This course prepares you to become a Certified Tableau for Data Analysis Expert. Tableau is a powerful tool that turns numbers into beautiful, interactive visualisations. With Tableau, you can tell stories with data β stories that help businesses and organisations make better decisions.
Whether you are a beginner who has never used Tableau or someone who wants to become a certified expert, this course will guide you step by step. You will learn how to connect to data, create charts, build dashboards, and share your insights. By the end, you will be ready to take the Tableau certification exam and use Tableau confidently in your work.
π― Who this is for: Aspiring data analysts, business analysts, data scientists, students, and professionals who want to master Tableau and earn a certification.
π Prerequisites: Basic understanding of spreadsheets (like Excel) and an interest in data. No prior Tableau experience is needed.
Tableau is a software platform that helps people see and understand data. It allows you to connect to almost any database, drag and drop to create visualisations, and share them with anyone. Instead of looking at rows and columns of numbers, you can create charts, maps, and dashboards that tell a clear story.
Tableau is used by companies like Amazon, Netflix, and many Nigerian businesses to make data-driven decisions. It is one of the most in-demand skills in data analysis today.
This course covers everything you need to know to become a Tableau expert. Each module includes video lessons, hands-on exercises, and practical projects.
Get started with Tableau and understand its purpose.
Learn how to connect and prepare data for analysis.
Create your first charts and visualisations.
Learn to filter and organise your data.
Create powerful calculations to analyse data.
Build interactive dashboards and stories.
Create maps and analyse geographic data.
Explore advanced analytics features.
Tableau Desktop Specialist (Exam)
Tableau Certified Data Analyst (Exam)
π Study Tips:
Most candidates benefit from 4β6 weeks of consistent study. Below is a suggested plan:
| Week | Topics to Cover |
|---|---|
| Week 1 | Introduction, data connection, basic charts |
| Week 2 | Filters, sorting, grouping, and calculations |
| Week 3 | Dashboards, stories, maps |
| Week 4 | Advanced analytics, practice exams, and review |
π Certified Tableau for Data Analysis Expert β Complete Course Outline
References: Tableau Official Certification Guide Β· Tableau Community
Hello, future data expert! This module is your very first step into the world of Tableau, a magical tool that turns boring numbers into colourful, moving pictures β we call them charts and dashboards. Just like a painter uses a brush, you will use Tableau to tell stories with data. By the end of this module, you will understand what Tableau is, why it is so helpful, and how to start your very first project. Letβs begin our adventure!
In a small village in Lagos, there was a fruit seller named Chidi. Every day, he sold mangoes, oranges, and bananas. But one week, his mangoes started disappearing! π± Chidi was confused. He wrote down how many mangoes he sold each day: Monday 10, Tuesday 8, Wednesday 12, Thursday 6, Friday 15. He stared at the numbers, but they didnβt tell him anything. Then his friend Amina said, βLetβs put these numbers into Tableau!β She made a colourful bar chart. Suddenly, Chidi saw that Thursday had the fewest mangoes sold. Then he remembered that Thursday was market day β many people were buying from other stalls! The chart helped him solve the mystery. From that day, Chidi used Tableau to understand his sales and make better decisions. You too can be a data detective! π΅οΈββοΈ
Data is just a fancy word for information. Information can be numbers, words, or even pictures. When you count how many friends are in your class, thatβs data. When you write down the temperature every morning, thatβs data. Tableau helps us organise and show this data so we can understand it better.
π Data is everywhere! - Your age (number) - Your name (word) - Your favourite colour (word) - How many steps you take (number)
Mini summary: Data = information. Tableau works with data.
Tableau is a computer program that helps you see data in many fun ways. It makes charts, maps, and dashboards. Think of it like a magic magnifying glass that shows you hidden patterns. If you have a list of your favourite foods and how much you like them, Tableau can draw a bar chart that shows which food is number one!
Tableau = Data + Pictures = Understanding
Mini summary: Tableau turns data into pictures so we can understand it quickly.
We analyse data to answer questions. For example: βWhich month is hottest?β or βWhich game is most popular?β Analysis means looking closely at data to find answers. Tableau makes analysis easy because you can drag and drop β just like building with blocks!
Question β Data β Tableau Chart β Answer!
Mini summary: Analysis = finding answers in data.
When you open Tableau, you see a workspace. It has a Data pane (where your data lives), a Shelves area (where you put fields), and a Canvas (where your chart appears). Itβs like your art studio: the paint is your data, the brushes are the shelves, and the canvas is where the magic happens.
+-----------------------+ | Tableau Workspace | | +------+ +--------+ | | | Data | | Canvas | | | | pane | | (chart)| | | +------+ +--------+ | | +------------------+ | | | Shelves (Rows, | | | | Columns, Filters) | | | +------------------+ | +-----------------------+
Mini summary: Workspace = data pane + shelves + canvas.
Before you can make a chart, you need to connect to your data. This is like opening a book before you read it. Tableau can connect to Excel files, text files, and even databases. You just click βConnectβ and choose your file. Easy peasy!
Step 1: Open Tableau Step 2: Click βConnectβ Step 3: Choose your file (e.g., Sales.xlsx) Step 4: Your data appears in the Data pane
Mini summary: Connect = open your data file in Tableau.
In Tableau, every piece of data is either a dimension or a measure. Dimensions are categories β like βFruitβ (mango, orange, banana). Measures are numbers β like βSalesβ (β¦100, β¦200). Dimensions are usually words, and measures are numbers. Tableau automatically puts them in the right place.
Dimensions (categories) Measures (numbers) βββββββββββββββββββββ ββββββββββββββββ Fruit Sales (β¦) City Temperature Month Score
Mini summary: Dimensions = categories, Measures = numbers.
A bar chart is a chart with bars (rectangles). The taller the bar, the bigger the number. Letβs make one! Drag a dimension (like βFruitβ) to Columns, and a measure (like βSalesβ) to Rows. Tableau draws the bars automatically. You can change colours, add labels, and make it beautiful.
Sales (β¦)
400 | ββββ
300 | ββββ ββββ ββββ
200 | ββββ ββββ ββββ
100 | ββββ ββββ ββββ
0 +βββββββββββββββββ
Mango Orange Banana
Mini summary: Bar chart = bars show values.
A line chart connects points with a line. It is perfect for showing trends over time β like sales each month. Drag a date field to Columns and a measure to Rows. Tableau draws the line. You can see if things go up (increase) or down (decrease).
Sales
500 | *------*
400 | / \
300 | * *
200 | \
100 | *
0 +βββββββββββββββββ
Jan Feb Mar Apr
Mini summary: Line chart = shows change over time.
Sometimes you want to see the biggest or smallest values first. Sorting arranges your data in order (AβZ or smallestβlargest). Filtering lets you focus on a part of your data β like only βMangoβ sales. Just click the sort icon or drag a field to the Filter shelf.
Before sorting: Mango(100), Banana(300), Orange(200) After sorting: Banana(300), Orange(200), Mango(100) [largest first]
Mini summary: Sort = order your data. Filter = pick a piece.
A dashboard is like a big board where you place many charts together. You can see everything at once β like a pilotβs cockpit! You can put a bar chart, a line chart, and a map all on one dashboard. It helps you tell a complete story.
+βββββββββββββββββββββββββββββββββββββββββββββ+ β π DASHBOARD: Fruit Sales β β +ββββββββββ+ +ββββββββββ+ +ββββββββββ+ β β β Bar chartβ β Line chartβ β Map β β β β β β β β β β β +ββββββββββ+ +ββββββββββ+ +ββββββββββ+ β β Filters: Fruit βΌ β +βββββββββββββββββββββββββββββββββββββββββββββ+
Mini summary: Dashboard = many charts on one page.
Once your dashboard is ready, you can share it with others. You can print it, save it as a picture, or publish it to Tableau Public (a free website). Your friends and family can see your awesome charts!
Share options: 1. Save as image (.png) 2. Print 3. Publish to Tableau Public 4. Send the workbook (.twb)
Mini summary: Sharing = let others see your data story.
Tableau Public is a free version of Tableau. You can use it to create and share charts on the internet. Many people use it to show data about sports, music, weather, and more. You donβt need to pay anything β just sign up and start creating!
Tableau Public = Free + Online + Shareable
Mini summary: Tableau Public = free version for everyone.
Data comes in different types: - Numbers (e.g., 5, 100) - Text (e.g., βMangoβ, βLagosβ) - Dates (e.g., 2026-07-04) Tableau handles them automatically. Dates are special because they can be grouped by year, month, or day.
Number: 42 Text: "Chidi" Date: 2026-07-04
Mini summary: Data types = number, text, date.
Aggregation means combining numbers. Common aggregations: - SUM β add all numbers. - AVG β find the average. - COUNT β count how many items. Tableau does these calculations for you with one click.
Sales: 100, 200, 300 SUM = 600 AVG = 200 COUNT = 3
Mini summary: Aggregation = combine numbers (sum, avg, count).
Always save your work! Click βFileβ β βSaveβ. Give your file a name like βMy First Dashboardβ. You can also save it to Tableau Public so you can open it from any computer.
Save as: .twb (workbook) or .twbx (packaged)
Mini summary: Save = keep your work safe.
Bar Chart (Sales)
400 | β β β β
300 | β β β β β β β β β β β β
200 | β β β β β β β β β β β β
100 | β β β β β β β β β β β β
0 +ββββββββββββββ
Mango Orange Banana
Line Chart (Trend)
500 | *
400 | / \
300 | * *
200 | \
100 | *
0 +ββββββββββ
Jan Feb Mar Apr
Dashboard Layout +ββββββββββββββββββββββββββββββ+ | π DASHBOARD | | +ββββββββ+ +ββββββββββββ+ | | |Bar | |Line | | | |chart | |chart | | | +ββββββββ+ +ββββββββββββ+ | | +ββββββββββββββββββββββββ+ | | | Map | | | +ββββββββββββββββββββββββ+ | +ββββββββββββββββββββββββββββββ+
| Dimension | Measure |
|---|---|
| Fruit (Mango, Orange) | Sales (β¦100, β¦200) |
| City (Lagos, Abuja) | Population (millions) |
| Month (January, February) | Temperature (Β°C) |
| Bar Chart | Line Chart |
|---|---|
| Shows categories (e.g., fruits) | Shows trends over time |
| Bars are separate | Points connected by line |
| Best for comparing groups | Best for seeing change |
Congratulations! You have completed Module One. You learned that data is information, and Tableau is a tool that turns data into colourful charts. You discovered the workspace, how to connect to data, and how to build bar and line charts. You also learned about dimensions, measures, dashboards, and sharing. Remember: Tableau is your superpower to see the hidden stories in numbers. Keep practicing, and you will become a data analysis expert!
Match the term with its definition:
| Term | Definition |
|---|---|
| 1. Dimension | A. Number like sales |
| 2. Measure | B. Category like fruit |
| 3. Dashboard | C. Many charts on one page |
| 4. Filter | D. Show only some data |
Answers: 1-B, 2-A, 3-C, 4-D
In groups of 3, collect data on your favourite snacks (name, number of votes). Use Tableau to create a bar chart. Present it to the class.
Find a simple dataset (e.g., monthly rainfall). Open Tableau Public and create a line chart. Save it and share the link with your teacher.
βMy Favourite Thingsβ β Collect data from 10 classmates about their favourite colour, food, and sport. Create a dashboard with three charts (bar, pie, or line). Present it to the class.
Download a sample Excel file from the internet (or use the one provided). Connect it to Tableau Public. Create a bar chart, a line chart, and a dashboard. Submit the link to your teacher.
Find a dataset about Nigerian states (population, area). Create a map chart in Tableau. Show which state has the largest population. Share your map with the class.
Answers for Fill-in-the-Blank: 1. information, 2. pictures, 3. dimension, 4. measure, 5. dashboard.
Answers for True/False: 1. False, 2. False, 3. False, 4. True, 5. True.
In the next module, we will dive deeper into connecting to different data sources, cleaning data, and creating advanced charts like pie charts and scatter plots. You will also learn how to add calculations to your data. Make sure you have Tableau Public installed and ready!
End of Module One β You are now a Tableau beginner! π
Welcome, young data explorer! π This is the first module of your journey to becoming a Certified Tableau for Data Analysis Expert. You might be wondering: βWhat is data? What is Tableau? Why should I care?β This module will answer all those questions in the simplest way possible β like we are talking to a 10βyearβold friend. We will learn what data is, why it is important, and how Tableau helps us turn boring numbers into colourful pictures called visualisations. By the end, you will be able to look at data like a detective and tell stories with it!
After this module, you will be able to:
At Sunshine School, the canteen served three types of lunch: Jollof rice, Beans and plantain, and Chicken and chips. The head teacher, Mrs. Ade, noticed that sometimes there was too much food left, and other times students went hungry. She asked the clever students in the βData Clubβ to help. They collected numbers: every day they wrote down how many students chose each meal. After one week, they had a table of numbers β thatβs data! But the numbers were confusing. So they used a tool (like Tableau!) to turn the numbers into colourful bar charts. They saw that Jollof rice was the favourite on Mondays, but Chicken and chips was the best on Fridays. Now Mrs. Ade knew exactly how much to cook each day. No more waste, no more hungry children! That is the power of data and visualisation. And that is exactly what we will learn.
Definition: Data is just a fancy word for information. It can be numbers, words, pictures, or even sounds.
Why important? Without data, we cannot know what is happening around us.
Simple explanation: Think of data as clues in a detective story.
Real-life example: The temperature outside is 30Β°C β that is data.
School example: Your test score (85%) is data.
Home example: The number of spoons in the kitchen drawer (12) is data.
Nigerian example: The price of a bag of rice (#65,000) is data.
Illustration:
π DATA = INFORMATION - numbers: 7, 15, 200 - words: "rainy", "hot" - pictures: π§οΈ, βοΈ
Mini summary: Data is information that helps us understand things.
Definition: Analysis means studying data carefully to find answers.
Why important? It helps us make smart decisions.
Simple explanation: Like looking at all the clues to solve a puzzle.
Real-life: A doctor checks your temperature (data) to know if you are sick.
School: Teachers look at test scores to see which subject needs more practice.
Home: Parents check how much money they spent on food to plan the next month.
Nigerian: The government analyses rainfall data to plan for farming.
Illustration:
Data β π Analyse β π‘ Answer / Decision
Mini summary: We analyse data to find hidden patterns and make good choices.
Definition: Tableau is a computer program that turns data into beautiful pictures (charts, maps, graphs).
Why important? It makes data easy to understand β even for a 10βyearβold!
Simple: Tableau is like a magic paintbrush for numbers.
Real-life: A shop owner uses Tableau to see which products sell best.
School: You can use Tableau to show your class how many students like Mathematics.
Home: You can show your family how much water you drink each day.
Nigerian: A bank in Lagos uses Tableau to see which branches have the most customers.
Illustration:
π Tableau | V π π πΊοΈ (charts and maps)
Mini summary: Tableau is a tool that turns data into colourful pictures.
Definition: Raw data is just numbers or words without any picture. A visualisation is a chart or graph that shows data in a picture.
Why important? Pictures help our brains understand faster.
Simple: Raw data is like a messy room; visualisation is like organising everything on shelves.
Real-life: A list of 1000 sales numbers is raw data. A bar chart of those sales is a visualisation.
School: A list of marks is raw; a pie chart of grades is visual.
Home: A shopping list is raw; a picture of how much you spent on fruits vs vegetables is visual.
Nigerian: A table of exam results is raw; a map showing states with best scores is visual.
Illustration:
Raw data: 5, 8, 12, 3, 9 Visualisation: π Bar chart
Mini summary: Raw data is plain; visualisation is a picture of the data.
Definition: A bar chart uses rectangular bars to show numbers.
Why important? It helps compare different things easily.
Simple: Like different lengths of chocolate bars β the longer the bar, the bigger the number.
Real-life: Comparing sales of different iceβcream flavours.
School: Comparing the number of boys and girls in each class.
Home: Comparing how much time you spend on homework vs games.
Nigerian: Comparing the population of Lagos, Kano, and Rivers states.
Illustration:
10 | ββββββββ
8 | ββββββ
6 | ββββ
4 | ββ
2 | β
Apples Oranges Bananas
Mini summary: Bar charts compare amounts with bars.
Definition: A pie chart is a circle divided into slices like a pizza. Each slice shows a part of the whole.
Why important? It shows proportions β how much each part takes.
Simple: If you have a pizza and eat 2 of 8 slices, that is 25% β shown in a pie chart.
Real-life: Showing what percentage of your day you spend sleeping, studying, playing.
School: Showing how many students prefer Mathematics, English, Science.
Home: Showing the proportion of your pocket money spent on snacks, toys, savings.
Nigerian: Showing the proportion of crops grown in Nigeria (cassava, yam, maize).
Illustration:
π (circle)
/ \
/ 25%\
| 50% |
\ 25%/
\ /
Mini summary: Pie charts show parts of a whole.
Definition: A line chart shows trends over time by connecting points with a line.
Why important? It shows if something is going up, down, or staying the same.
Simple: Like drawing a line of your height every year β it shows how you grow.
Real-life: Tracking temperature every day for a week.
School: Tracking your test scores over the term.
Home: Tracking how many times you watered the plant each day.
Nigerian: Tracking the price of tomatoes over 6 months.
Illustration:
high *
| *
medium | *
| *
low | *
1 2 3 4 5 (days)
Mini summary: Line charts show changes over time.
Definition: Data can be numbers (like 10, 25) or categories (like colours, names).
Why important? Tableau treats them differently.
Simple: Numbers are for maths; categories are for grouping.
Real-life: Height (number) and eye colour (category).
School: Age (number) and class (category).
Home: Number of family members (number) and favourite food (category).
Nigerian: State population (number) and state name (category).
Illustration:
Numbers: 7, 15, 200 Categories: "red", "Nigerian", "Jollof"
Mini summary: Data is either numbers (quantitative) or categories (qualitative).
Definition: In Tableau, a sheet is where you make one chart. A dashboard is a collection of many sheets placed together.
Why important? Dashboards tell a complete story.
Simple: A sheet is like one page in a comic; a dashboard is the whole comic book.
Real-life: A school dashboard shows attendance, grades, and sports together.
School: A sheet for class marks, another for attendance; combine into dashboard.
Home: A sheet for chores done, one for pocket money; combine.
Nigerian: A dashboard for a hospital showing patients, medicines, and doctors.
Illustration:
Sheet 1 (Bar chart) + Sheet 2 (Pie chart) = Dashboard (both together)
Mini summary: Sheets are single charts; dashboards combine them.
Definition: Tableau is cool because it is interactive β you can click, hover, and filter to see different views.
Why important? It lets you explore data like a video game.
Simple: Like zooming in on a map.
Real-life: Click on a bar to see which products sold best in a city.
School: Click on a class to see the students' names.
Home: Click on a day to see what you ate.
Nigerian: Click on a state to see its agricultural output.
Illustration:
[Filter] β [Bar chart] β click β [details]
Mini summary: Tableau lets you play with data by clicking and exploring.
Definition: Telling a story with data means explaining what the charts mean.
Why important? People remember stories better than numbers.
Simple: Instead of saying βsales are 50β, say βWe sold 50 more iceβcreams because it was sunny!β
Real-life: A news report showing how rain affects harvest.
School: βOur class read more books in March, so we had a party.β
Home: βI drank more water, so I felt better.β
Nigerian: βIn the north, more cows were sold because of the festival.β
Illustration:
Data (numbers) β Chart β Story (explanation)
Mini summary: Data storytelling turns numbers into a story people understand.
Definition: A data source is where data comes from: Excel, databases, or even a simple list.
Why important? Tableau needs data to work.
Simple: Like a chef needs ingredients.
Real-life: Sales data from a shopβs computer.
School: A class list from the teacher.
Home: A list of monthly bills.
Nigerian: Data from the National Bureau of Statistics.
Illustration:
π Excel β Tableau β Chart
Mini summary: Data sources are the raw ingredients for Tableau.
Definition: A filter hides some data so you can focus on what you want.
Why important? It helps you zoom in.
Simple: Like wearing sunglasses to see only bright things.
Real-life: Show only sales from January.
School: Show only students who scored above 70%.
Home: Show only snacks you bought.
Nigerian: Show only states in the south.
Illustration:
All data β [Filter] β only Nigeria data
Mini summary: Filters let you focus on specific parts of the data.
Encourage students to bring any list (e.g., favourite fruits) and help them create simple bar charts manually. Emphasise that Tableau does the drawing β we just need to tell it what to draw. Use the warmβup story to spark curiosity.
Ask your child: βWhat data did you see today?β Help them count items at home β spoons, books, clothes β and make simple charts on paper. This builds a dataβminded family.
Did you know that Tableau can connect to data from the internet? For example, it can get live weather data and show it on a map!
π Raw Data
|
V
π Tableau
|
V
π Chart / Dashboard
|
V
π Story / Decision
Raw: 20, 35, 15, 40
Visual:
40 | ββββββββ
30 | ββββββ
20 | ββββ
10 | ββ
A B C D
| Chart Type | Best for | Example |
|---|---|---|
| Bar chart | Comparing categories | Sales by product |
| Pie chart | Showing proportions | Market share |
| Line chart | Showing trends over time | Temperature over week |
| Data Type | Description | Example |
|---|---|---|
| Numeric | Numbers that can be added | Age, height |
| Categorical | Labels or groups | Colour, city |
We have learned that data is everywhere β in school, home, and Nigeria. Tableau is a powerful tool that turns data into beautiful charts and dashboards. We explored bar, pie, and line charts, and learned how to tell stories with data. Remember: data helps us make better decisions. You are now ready to start your journey as a data analyst!
| Term | Definition |
|---|---|
| 1. Tableau | A. Shows parts of a whole |
| 2. Bar chart | B. Tool for visualisation |
| 3. Pie chart | C. Compares categories with bars |
| 4. Line chart | D. Shows trends over time |
| 5. Dashboard | E. Collection of charts |
Answers: 1-B, 2-C, 3-A, 4-D, 5-E
Scenario: A school wants to know which lunch meal is most popular. They collected data for a week. How would you use Tableau to help them? Which chart would you use and why?
Scenario 2: A farmer in Nigeria wants to track rainfall every month. Which chart is best and why?
In groups of 4, collect data on your favourite fruits. Make a bar chart on paper. Then, present your chart and tell a story about it.
List 10 items in your room (books, toys, clothes). Count how many are red, blue, green, etc. Draw a pie chart.
Using Tableau Public (or a drawing), create a dashboard with 3 charts about your class: favourite subject, number of boys/girls, and attendance. Show it to your class.
Download the sample dataset from the school (or use a simple list) and create a bar chart and a line chart in Tableau. Write a short paragraph explaining what each chart shows.
Create a dashboard that tells a story about βMy Weekβ. Include a bar chart of activities, a pie chart of time spent, and a line chart of happiness each day.
Fill-in-the-Blank: 1. information 2. charts 3. pie 4. bar 5. line
True/False: 1.F 2.F 3.F 4.T 5.F
Multiple Choice: 1B, 2B, 3C, 4B, 5B, 6B, 7B, 8A, 9A, 10B, 11B, 12A, 13B, 14A, 15B
In the next module, we will dive deeper into Tableauβs interface. We will learn how to connect to real data sources, create more advanced charts, and build interactive dashboards. Get ready to become a data wizard!
Module One complete! You have taken the first step to becoming a Tableau expert. Well done! π
Β© 2025 Β· Data Analysis Expert Course Β· Module One
Part of the "Certified Tableau for Data Analysis Expert" Course
Welcome, young data explorer! You have already learned how to connect data and make simple pictures with numbers. Now it is time to make those pictures look beautiful and tell amazing stories. In this module, you will become a chart artist. You will learn how to choose the right chart, how to add colors, labels, and how to organize your work so everyone says "Wow!" when they see it.
Imagine you have a box of crayons. You can draw a sun, a tree, or a house. But if you just scribble, nobody knows what it is. Data analysis is the same. We must draw our numbers neatly so people can understand them. This module will teach you how to draw neat, colorful, and smart charts using Tableau. By the end, you will be able to take any pile of numbers and turn it into a clear picture that tells a story. Let us start our art class!
By the time you finish this module, you will be able to:
Once upon a time in Lagos, there was a school called Sunshine Academy. The school decided to have a Great Cake Contest. Three friends, Tunde, Amara, and Chidi, each baked a cake. After the contest, the judges counted the votes from 100 students.
Tunde got 45 votes. Amara got 35 votes. Chidi got 20 votes. The principal, Mrs. Obi, wanted to show the results during the morning assembly. She wrote the numbers on a big piece of paper. Tunde (45), Amara (35), Chidi (20). But when she held it up, the students in the back could not see the numbers clearly. Some shouted "Who won?" Others thought Amara won because her name was in the middle.
Then a smart student named Ada said, "Mrs. Obi, can we draw a picture of the numbers? We can make three columns. The tallest column will be Tunde, then Amara, then Chidi. Even a small child can see who is the winner without reading the numbers!" Mrs. Obi loved the idea. They made a bar chart using cardboard. The Tunde column was the highest. Everybody clapped. Tunde got his trophy, and the school learned that a picture of numbers is worth a thousand words. Ada had just become the school's first data analyst!
Today, you will be just like Ada. You will learn to make those pictures, which we call charts or graphs, on a computer using Tableau.
Definition: A chart is a drawing that shows numbers. It uses shapes like bars, lines, or circles to make numbers easy to compare.
Why it is important: Our eyes are very good at seeing size differences. A chart helps us spot the biggest, the smallest, and patterns very fast. Without charts, numbers stay hidden in long lists and tables.
Simple Explanation: Think of a chart as a picture book for numbers. Instead of reading "45, 35, 20", you see three bars. The longest bar is the winner. That is a bar chart.
Real-life Example: A weather report on TV shows a line that goes up and down to show how hot it will be this week.
School Example: A teacher sticks a chart on the wall showing how many gold stars each group earned. Group A has 10 stars (tall bar), Group B has 7 stars (shorter bar).
Home Example: Your mom draws a circle to show the family budget. A big slice for food, a small slice for sweets.
Nigerian Example: At a market in Onitsha, a yam seller draws a chart on a board showing the price of yams every month. When the line goes up, yams are expensive during the dry season. When it goes down, yams are cheaper during harvest.
Yam Price Chart (Simple Bar Idea)
Price (Naira)
|
800 | *****
600 | ***** * *
400 | ***** * * * *
200 | * * * * * *
0 |------------------------
Jan Feb Mar Apr
Mini Summary: A chart turns numbers into shapes. It helps our brain understand data quickly. It is a universal language everyone can read.
Definition: There are many chart types. The four best friends you must know are Bar Chart, Line Chart, Pie Chart, and Scatter Plot.
Why it is important: Each friend has a special job. Using the wrong chart is like using a spoon to cut meat. It works badly and confuses people.
| Chart Type | Best Job | Looks Like | Question it Answers |
|---|---|---|---|
| Bar Chart | Comparing different groups | Tall and short towers | Which class has the most students? |
| Line Chart | Showing change over time | A mountain path going up and down | How did the rainfall change from January to June? |
| Pie Chart | Showing parts of a whole | A pizza cut into slices | What fraction of my pocket money do I spend on snacks? |
| Scatter Plot | Finding relationships between two things | Dots sprayed on a field | Does studying longer improve test scores? |
Real-life Example: A sports coach uses a bar chart for points of teams, a line chart for a runner's speed, and a pie chart for the percentage of wins, draws, and losses.
Nigerian Example: A farmer uses a line chart to see the growth of his chickens over 6 weeks. He uses a bar chart to compare the eggs laid by different chicken breeds: Oyo breed vs. Fulani breed.
Chicken Growth (Line Chart)
Weight (kg)
3 | *
2 | *----
1 | *----
0 |----*----*----*----
W1 W2 W3 W4 (Weeks)
Mini Summary: Bar for compare, Line for time, Pie for parts, Scatter for relationships. Remember these four friends well.
Definition: A bar chart uses rectangles (bars) of different heights to compare values. The longer the bar, the bigger the value.
Why it is important: It is the most common and easiest chart to read. Even a 4-year-old can see which bar is the tallest.
Simple Explanation: Imagine stacking blocks. Tunde stacked 5 blocks, Amara stacked 3. The bar for Tunde is 5 blocks high. Easy.
Real-life Example: A mobile phone shop shows bars for phones sold: Samsung (20), iPhone (15), Nokia (10). The Samsung bar is the tallest.
School Example: Comparison of library books read by Primary 3A, 3B, and 3C.
Home Example: Comparing the amount of water (in litres) your family drinks each day of the week.
Nigerian Example: Comparing the number of passengers using different transport in Abuja: Keke Napep (200), Danfo bus (500), Okada (150). The Danfo bar is the tallest.
Transport Passengers in Abuja
Keke: |********** (200)
Danfo: |************************* (500)
Okada: |******* (150)
Each * represents 20 passengers.
Tableau Tip: In Tableau, you drag the thing you are comparing to Columns, and the number to Rows. Tableau draws the bars automatically. Click "Swap" to turn them sideways.
Mini Summary: Bar charts are the champions of comparison. Always label your bars clearly. Start the number line at zero so the sizes do not lie.
Definition: A line chart connects dots of data with a line. The line moves from left to right, usually showing time.
Why it is important: It is perfect for seeing trends. A trend is a pattern over time, like something going up, down, or staying flat.
Simple Explanation: Put a dot for your height every birthday. Age 5: 100cm, Age 6: 110cm. Connect the dots. The line goes up. That is a growth trend.
Real-life Example: A stock market graph on the news. The line goes crazy up and down. If the line goes up, people are happy.
School Example: Tracking the temperature outside the classroom every morning for a month. Draw a line connecting the dots.
Home Example: Your dad records the NEPA (electricity) hours per day for a week. Monday: 4 hours, Tuesday: 2 hours, Wednesday: 0 hours. The line crashes down on Wednesday.
Nigerian Example: The Central Bank of Nigeria watches the dollar-to-naira exchange rate line chart. If the line goes up fast, the naira is getting weaker.
Naira to Dollar rate (Line Chart)
Rate (N)
1500 | *
1000 | *-----*
500 | *-----*
0 |----------------
Jan Feb Mar
This line is climbing up. Uh oh!
Tableau Tip: You need a date field to make a proper line chart. Drag the Date to Columns, and the Number to Rows. Tableau connects the dots for you.
Mini Summary: Line charts tell a story of change. "First it was this, then it became that."
Definition: A pie chart is a circle cut into slices. The whole circle is 100%. Each slice shows a part of that 100%.
Why it is important: It shows how a total amount is divided. It answers the question "What fraction of the whole is this?"
Simple Explanation: If you have a meat pie and you give 50% to your brother, the pie is cut into two halves. The brother's slice is huge. If you give 10% to your sister, her slice is small.
Real-life Example: A phone battery icon. When it is full, it is a full circle. When half empty, half the circle is empty. That is a pie chart.
School Example: Show the favorite fruits of 20 students. 10 like oranges (half the circle), 5 like bananas (quarter), 5 like apples (quarter).
Home Example: How you spend 24 hours. Sleep: 8 hours (big slice), School: 6 hours (medium slice), Play: 3 hours (small slice), Eating: 2 hours (tiny slice).
24 Hours Pie Chart
______
/ Eat \ (Small slice)
| Sleep | (Biggest slice)
\ Play / (Medium)
\School/ (Medium)
------
Nigerian Example: The budget of a state government. The pie chart shows a huge slice for Education, smaller slices for Health and Roads. Citizens can see where the money goes.
Important Warning: Use pie charts only when the parts add up to 100%. Never use them if you have 10 slices, it becomes a messy pizza. Use a bar chart instead.
Mini Summary: Pie charts show parts of a whole. Keep the slices few and big. Label them with percentages.
Definition: A scatter plot uses dots to show two different numbers for many items. It shows if there is a relationship between the two numbers.
Why it is important: It helps us answer "Does one thing affect the other?" Doctors use it. Scientists use it.
Simple Explanation: You ask, "Do tall children have bigger feet?" Measure 10 friends. Height on the bottom (X-axis), shoe size on the side (Y-axis). Put a dot for each friend. If the dots go up a hill (bottom-left to top-right), then yes, tall children generally have bigger feet!
Real-life Example: A car website shows a scatter plot. The bottom is car price, the side is car speed. You find that expensive cars are often faster.
School Example: Do students who eat breakfast get higher test scores? Dots for students who ate breakfast are mostly high up on the score side. Dots for hungry students are lower.
Home Example: Does the amount of water you give a plant affect how tall it grows? More water (x) might mean taller plant (y), but too much water makes it die (dots go down).
Nigerian Example: A researcher in Lagos plots the distance from a dump site against the number of mosquitoes in a house. Houses closer to the dump have more mosquitoes (dots cluster high on the left). Houses far away have few mosquitoes (dots low on the right).
Distance vs Mosquitoes (Scatter)
Mosquitoes |
50 | * *
40 | * * *
30 | * *
20 | * *
10 | * *
|___________________
Near Far Distance
The dots go down. That means distance helps!
Tableau Tip: Drag one number to Columns, one number to Rows. If you drag a category (like Names) to "Detail", you get a dot for each person.
Mini Summary: Scatter plots are dots looking for friends. If they clump together in a line, the two numbers are related.
Definition: The "Marks" card in Tableau is a toolbox for painting your chart. You can change colors, sizes, shapes, and labels here.
Why it is important: A black and white chart is boring. Colors make it fun and help highlight important things. A red bar for danger, green for good.
Simple Explanation: Think of a coloring book. You have the outlines (the bars). The Marks card gives you the crayons. Drag a "Color" crayon onto the outline to fill it.
Real-life Example: A traffic light. Red means stop (bad), Green means go (good). Your brain understands colors faster than words.
School Example: You make a bar chart of test scores. You color the passing students green and the failing students red. Instantly, the teacher sees the red bars and knows who needs help.
Home Example: You list your chores. You color finished chores blue and pending chores orange. Mom sees a lot of orange and says "Finish your chores!"
Nigerian Example: A chart showing state populations. You can color the states by geopolitical zone (South-West in yellow, South-East in green, North-West in purple). The map of Nigeria becomes a rainbow of data.
| Subject | Score | Color Code | Meaning |
|---|---|---|---|
| Mathematics | 85 | Green | Excellent |
| English | 55 | Red | Needs Help |
| Science | 70 | Orange | Average |
Mini Summary: Colors are like spices. They make the data tasty. But do not use too many colors, or it becomes confusing like a clown's suit.
Definition: Labels are text pieces attached to the bars, slices, or points showing the exact number. A Title is the big headline of the chart.
Why it is important: A chart without a title is like a book without a name. Labels save people from guessing the height of a bar. They can read "45" exactly.
Simple Explanation: If you draw a birthday card, the picture is the chart. The words "Happy Birthday" are the title. The small words explaining the joke are the labels.
Real-life Example: A map has labels showing street names. Without them, you are lost. A chart without labels makes you lost too.
School Example: The chart title is "Total Football Goals Scored in Term 1". The labels on top of the bars say "15", "12", "20".
Home Example: Your chore chart title is "Chore Heroes of the Week". The labels next to your name say "Made bed 7 times".
Nigerian Example: A chart from the National Bureau of Statistics. The title is "Unemployment Rate in Nigeria (2020-2024)". The labels on the line show the exact percentage at each point, like 33.3%.
Tableau Tip: Drag a measure from the Data pane onto the "Label" shelf in the Marks card. Double-click the title "Sheet 1" at the top to rename it to something cool.
Mini Summary: Always title your chart. Always label the numbers if people need to know them exactly. Do not hide the numbers.
Definition: Sorting means arranging your data from highest to lowest (descending) or lowest to highest (ascending).
Why it is important: A sorted chart is much easier to read. Your eyes do not have to search for the tallest bar. It is right there on the left.
Simple Explanation: Imagine a class photo. If students do not line up by height, it looks messy. If the shortest is on the left and tallest on the right, it looks clean. Sorting data does the same.
Real-life Example: A music chart list. The number 1 song is at the top. The list is sorted by popularity.
School Example: The teacher sorts the spelling test results. From the highest score (Emeka, 10/10) down to the lowest (Ada, 5/10).
Home Example: You arrange your action figures from tallest to shortest.
Nigerian Example: A list of richest men in Africa. Aliko Dangote is sorted at the top, number 1. The bars in a chart should start with him at the top too.
Tableau Tip: Look at the toolbar. You will see icons with bars and an arrow pointing down (Sort Descending) or up. Click them to sort instantly.
Mini Summary: Sort the bars. It helps everyone find the top and bottom quickly. Order matters.
Definition: A filter hides some data and shows only the data you are interested in. It is like a magic curtain.
Why it is important: Sometimes you have too much data. If you want to look only at Lagos sales from 2024, a filter hides all other cities and years. It keeps you focused.
Simple Explanation: You have a big bag of Lego. You only want the red bricks. You filter out the blue, green, and yellow bricks. Now you see only the red ones.
Real-life Example: Online shopping. You filter by price "Less than 5000 Naira". The website hides the expensive phones and shows you the cheap ones.
School Example: The class list has all 100 students. You apply a filter for "Age = 10". Now you see only the 10-year-old students.
Home Example: Your mom looks at her phone contacts. She filters by "Family" to find Grandma's number quickly.
Nigerian Example: A company in Port Harcourt wants to see sales for only "Pounded Yam" products. They filter the product field to keep only Pounded Yam. The chart changes and shows only that data.
Tableau Tip: Drag a field from the Data pane into the "Filters" shelf. A box pops up. Click the things you want to keep. Then click OK. Watch the chart shrink to show only your selection.
Mini Summary: Filters help you zoom in. They hide the noise and show the signal. Use them to answer specific questions.
Definition: A dashboard is a single page that holds several charts and filters together. They work as a team.
Why it is important: One chart can answer one question. A dashboard answers a bigger question using many charts at a glance. The President looks at dashboards to understand the whole country.
Simple Explanation: A car's dashboard has a speedometer (a gauge chart), a fuel gauge (a pie chart), and a warning light (a color indicator). You do not look at three separate pages; you look at one panel.
Real-life Example: The dashboard of a video game. You see your health bar, your ammo count, and the mini-map. That is a dashboard.
School Example: The principal's dashboard. One chart for attendance, one for test scores, one for discipline cases. She sees the whole school health in 5 seconds.
Home Example: A family weather dashboard. One chart for temperature, one for rain chance, one for wind speed.
Nigerian Example: A Nollywood movie producer's dashboard. Chart 1: Ticket sales per cinema. Chart 2: Sales by State. Chart 3: Total revenue. All on one page.
Tableau Tip: Click the "New Dashboard" button (the square with a plus sign at the bottom). Drag your sheets (Charts) from the left into the big white space. If you add a filter to the dashboard, it can control all the charts at once!
Dashboard Layout
+---------------------------------------+
| TITLE: Movie Sales Report |
+---------------------------------------+
| FILTER: [Select Year: 2024] |
+-------------------+-------------------+
| Bar Chart of | Line Chart of |
| Sales by Cinema | Sales over Months |
| (Left) | (Right) |
+-------------------+-------------------+
Mini Summary: Dashboards are super-charts. They tell the full story. Place the most important chart on the top left. Place filters where everyone can find them.
Definition: A Story in Tableau is a sequence of worksheets or dashboards that walk you through a finding, step-by-step. Like a PowerPoint presentation.
Why it is important: Sometimes people need you to hold their hand and explain "First, look at this. Now, look at that." A story point captures the chart at that moment.
Simple Explanation: You are telling a detective story. Chapter 1: The crime scene (A map). Chapter 2: The suspects (A bar chart). Chapter 3: The verdict (A pie chart). Each chapter is a story point.
Real-life Example: A news report online. You scroll and see a chart, then another, then another. Each one explains a part of the event.
School Example: A science project presentation. Slide 1: The question. Slide 2: The experiment data. Slide 3: The conclusion chart.
Nigerian Example: A climate change report. Story Point 1: "Rainfall in Sokoto is going down." (Line chart going down). Story Point 2: "But flooding in Lagos is going up." (Bar chart showing flood incidents). Story Point 3: "We need to act." (Text box with a call to action).
Tableau Tip: Click the "New Story" button. Drag a sheet into the box. Click "Add a caption" to write what the chart says. Click "New Blank Point" to start the next chapter.
Mini Summary: Stories guide the viewer. Do not just throw charts at them. Take them on a journey from "What?" to "Why?" to "What now?".
Definition: A Highlight Table is a grid of numbers where the color of the cell changes based on how high or low the number is.
Why it is important: It is a mix of a table and a chart. You get the exact number, but the color helps your eyes instantly see hot spots (high values) and cold spots (low values).
Simple Explanation: Think of a football league table. The number 1 team has a bright green background. The last team has a red background. You see the color before you read the number.
Real-life Example: A weather map on TV. Temperatures are not just numbers; the map is colored blue for cold regions and red for hot regions. A highlight table does this for any data.
School Example: A marks sheet for a whole class. Columns are subjects, rows are names. Emeka's high scores are colored dark green. His low scores are light yellow. He quickly sees he is weak in History.
Nigerian Example: An investor looks at a table of bank stocks. The daily profit change is shown. High profit banks are colored deep green. Low profit or loss banks are colored red. The investor's eyes go straight to the green ones.
| Bank | Share Price (N) | Change |
|---|---|---|
| Zenith Bank | 45.00 | +5.00 |
| UBA | 25.00 | -2.00 |
| GTCO | 50.00 | +10.00 |
Mini Summary: Use highlight tables to make boring numbers beautiful. The color shows the size without needing a bar. It saves space.
Definition: These are errors that make your chart ugly or lying. Knowing them stops you from being a bad data analyst.
Why it is important: A bad chart is worse than no chart. It confuses people and might make them make wrong decisions. If a doctor reads a wrong chart, a patient might get hurt.
Mistake 1: The 3D Explosion. 3D charts look cool but are hard to read. The front slice looks bigger than the back slice. Stick to flat 2D charts.
Mistake 2: The Lying Axis. If you start a bar chart at 50 instead of 0, a small difference looks huge. A bar of 55 looks 5 times taller than a bar of 51. This lies to the eye. Always start bar charts at zero.
Mistake 3: The Junk Yard. Adding too many pictures, emojis, and irrelevant images to the background. Keep the chart clean. Data is the hero, not the background.
Mistake 4: Too Many Slices. A pie chart with 20 slices. The thin slices look like a spider web. Use a bar chart if you have more than 5 or 6 slices.
Lying Axis Comparison
True Scale (Starts at 0):
Apples: |************ (12)
Oranges: |********** (10)
(Difference looks small, 12 vs 10)
False Scale (Starts at 8):
Apples: |************ (12)
Oranges: |** (10)
(Difference looks massive, cheating!)
Mini Summary: Be honest with your data. Keep it flat, start at zero, and do not clutter the page. Simplicity is beautiful.
Definition: Combining everything you learned to make a final project.
Why it is important: Practice makes perfect. You will make a dashboard about your daily activities.
Step-by-Step Instructions:
Nigerian Example: Instead of just "My Day", make it "A Day at a Lagos Market". Time spent: Selling, Arranging goods, Talking to customers, Eating Amala.
"My Day" Dashboard Design
+----------------------------------------+
| A Day in the Life of Chidi |
+---------------------+------------------+
| [Pie Chart] | [Bar Chart] |
| Sleep 40% | Sleep ******* |
| School 30% | School ****** |
| Play 30% | Play ****** |
+---------------------+------------------+
| [Filter: Select Activity Type] |
| [Table of Exact Hours] |
+----------------------------------------+
Mini Summary: You are now a certified chart maker! A dashboard brings all your friends (Bar, Line, Pie) together to share a story.
Follow this recipe every time you open Tableau:
This module focuses on visual literacy. The goal is not just software memorization but the ability to decode and encode information visually. Encourage students to critique charts they see in the real world (newspapers, TV). Use the "Cake Contest" story as a recurring reference point. For the practical assignment, allow students to pick a topic they are passionate about (sports, music, food) to ensure engagement. The key challenge is stopping them from using 3D pie charts!
Dear Parents, you do not need to be a tech expert to help. Ask your child to explain their "My Day" chart to you. Ask them questions like "Which activity takes the biggest slice of your day?" or "Can you show me how your free time changed from Monday to Friday?". This reinforces analysis skills. Even a simple chart drawn with crayons based on household items (types of fruits in the bowl) reinforces the lesson. Praise the story behind the chart, not just the pretty colors.
Did you know that your brain processes pictures 60,000 times faster than text? That means reading a chart is like a super-fast shortcut for your brain. When you look at a red bar, you know it is "bad" before you even read the number. That is the power of a chart.
"A chart is a bridge between the data and the decision. Build strong, clear bridges."
Key Points to Never Forget:
When you get confused about which chart to use, follow this flowchart:
Start
|
V
Do you want to compare items?
|
+---- YES ----> BAR CHART
|
+---- NO -----> Do you want to see change over time?
|
+---- YES ----> LINE CHART
|
+---- NO -----> Do you want to see parts of a whole?
|
+---- YES ----> PIE CHART
|
+---- NO -----> Do you want to see if two things are related?
|
+---- YES ----> SCATTER PLOT
|
+---- NO -----> Use a simple TABLE
| Feature | Spreadsheet (Numbers Table) | Chart (Visual) |
|---|---|---|
| Speed of understanding | Slow. You must read every cell. | Fast. You see the tallest bar in 1 second. |
| Spotting Patterns | Hard. You might miss the upward trend. | Easy. The line clearly goes up. |
| Exact Values | Perfect. You see 45, not "about half". | Harder. You see a length. (Fix this with Labels!). |
| Best for | Doing math, calculating budgets. | Presenting to an audience, making decisions. |
Congratulations! You have finished Module Three. You are no longer just a data reader; you are a data artist. You learned that data without a chart is like music without a tune. You met the four best chart friends: Bar, Line, Pie, and Scatter. You learned how to color them, sort them, and place them on a dashboard. You learned the Nigerian secret to good data: keeping it clean, honest, and simple. Remember Ada and the cake contest. Every time you show a chart, you are helping someone see the story clearly. Great job!
Complete the sentences using the word bank: (Bar, Pie, Line, Scatter, Dashboard)
Answers are marked in bold.
Match the Chart Type with its Best Use.
| Column A (Chart) | Column B (Best Use) |
|---|---|
| 1. Bar Chart | A. Shows parts of a whole |
| 2. Line Chart | B. Finds relationships |
| 3. Pie Chart | C. Compares different groups |
| 4. Scatter Plot | D. Shows trends over time |
Answers: 1-C, 2-D, 3-A, 4-B
Objective: Understand how to describe a chart clearly.
Steps:
Empty your school bag. Count the items. Sort them into categories: Books, Stationery (pens/pencils), Lunch, Toys/Personal items.
Calculate the percentage for each category out of the total items. Draw a rough sketch of a pie chart on paper. Color the slices. Which slice is the biggest? Does that surprise you?
As a class, create a survey. Ask: "Favorite Food", "Favorite Subject", "Shoe Size", "Height". Enter the data into Tableau. Each student is responsible for creating one chart. Assign groups to build the Dashboard. Present it to another class. Teach them how to read the Bar Chart and Pie Chart.
This Saturday, keep a log of everything you do from 8:00 AM to 8:00 PM. Write down the Activity and Hours spent. On Monday, input this into Tableau. Create:
Go online or look in a newspaper/magazine. Find one example of a chart that you think is BAD. It might be too messy, a 3D pie, or lying. Screenshot it or cut it out. Bring it to class. Write down three reasons why it is bad and sketch how you would fix it in Tableau.
Fill-in-the-Blanks: 1. Pie, 2. Line, 3. Scatter, 4. Bar, 5. Dashboard
True or False: 1. False (Line is time), 2. True, 3. False (It can), 4. True, 5. False (Scatter uses dots).
Matching: 1-C, 2-D, 3-A, 4-B.
Get ready, Expert! You now know how to draw beautiful pictures. But what if the numbers themselves are messy or missing? In the next module, we will become Data Cleaners. We will learn how to fix broken data, remove duplicates, and fill in blanks so our charts become even more trustworthy. Think of it as washing the ingredients before you cook the meal. Bring your scrubbing brushes (keyboards) because things are about to get tidy!
End of Module Three. Well done!
Welcome, young explorer! In this module, we are going to learn how to turn boring numbers into exciting pictures and stories. Imagine you have a huge box of crayons and you want to show your friends what you did all week. Instead of just telling them, you draw a colourful picture. That is exactly what Tableau does β it takes data (numbers and facts) and turns them into beautiful charts, maps, and dashboards.
We will start from the very beginning. No scary words. We will use simple steps, lots of examples from home, school, and even Nigeria! By the end, you will be able to open Tableau, drag some fields, and create your very first chart. Ready? Let's go!
In a small village in Nigeria, there was a girl named Adaeze. Every day, she helped her grandmother sell oranges, mangoes, and bananas at the market. One day, her grandmother said, "Adaeze, I want to know which fruit sells the most so I can buy more of that fruit."
Adaeze wrote down every fruit she sold on a piece of paper. At the end of the week, she had a long list of numbers. It was so hard to understand! Then she remembered her teacher talking about pictures that show numbers. She drew a bar for each fruit β a tall bar for oranges, a medium bar for mangoes, and a short bar for bananas. Immediately, she could see that oranges were the winner! Her grandmother was so happy.
That is exactly what Tableau does β it takes your numbers and draws pictures so you can see the answer right away. Let's learn how to do that on a computer!
Definition: Data is just information. It can be numbers, words, or even pictures.
Why it is important: Without data, we cannot make good decisions. Data helps us know what is happening.
Simple explanation: Think of data like ingredients for a cake. You need flour, sugar, eggs β that is your data. Tableau is the oven that bakes a beautiful cake (chart).
Realβlife example: Your teacher has a list of all students' scores. That list is data.
School example: The number of books in the school library β that is data.
Home example: The temperature outside every morning β that is data.
Nigerian example: The number of people who watch Nollywood movies every week β that is data.
Illustration:
Data is like a box of LEGO pieces
π¦ π₯ π© π¨
Each piece is one fact (a number or name)
Tableau helps us build a castle out of them!
Mini summary: Data = information. Tableau uses data to create pictures.
Definition: Tableau is a computer program that turns data into colourful charts and maps.
Why it is important: It helps people see patterns and make smart decisions quickly.
Simple explanation: Tableau is like a magic paintbrush β you give it numbers, and it paints a picture that tells a story.
Realβlife example: A shop owner uses Tableau to see which products sell best.
School example: A principal uses Tableau to see which class has the best attendance.
Home example: You could use Tableau to track how many hours you play video games each day.
Nigerian example: A farmer in Kaduna uses Tableau to compare rainfall in different months.
Illustration:
Tableau = Magic Paintbrush ποΈ Numbers (data) β π¨ β Beautiful Chart
Mini summary: Tableau is a tool that makes data easy to understand through pictures.
Definition: In Tableau, every field is either a dimension or a measure.
Dimension: These are categories or labels. They are usually words (like "Fruit", "City", "Month").
Measure: These are numbers you can count or sum (like "Sales", "Quantity", "Temperature").
Why it is important: Tableau treats them differently. Dimensions split your data into groups, and measures are the values you want to calculate.
Simple explanation: Think of dimensions as the rows in a table (names) and measures as the columns with numbers.
Realβlife example: In a class, "Student Name" is a dimension; "Test Score" is a measure.
School example: "Subject" (Math, English) is a dimension; "Number of Students" is a measure.
Home example: "Day of the week" is a dimension; "Minutes spent reading" is a measure.
Nigerian example: "State" (Lagos, Kano) is a dimension; "Population" is a measure.
Illustration:
+-------------------+-------------------+ | DIMENSION | MEASURE | | (Categories) | (Numbers) | +-------------------+-------------------+ | Fruit | Quantity sold | | City | Temperature | | Month | Total Sales | +-------------------+-------------------+
Mini summary: Dimensions are labels; measures are numbers. Tableau uses both to build charts.
Definition: Connecting means telling Tableau where your data is stored (like an Excel file or a database).
Why it is important: Tableau cannot show pictures until you give it data.
Simple explanation: It is like opening a treasure box to take out the gold coins (data).
Realβlife example: You download a sales file from your company and open it in Tableau.
School example: Your teacher gives you a CSV file with students' marks; you connect Tableau to it.
Home example: You type your weekly allowance into Excel, then connect Tableau to that file.
Nigerian example: A health worker connects Tableau to a database of vaccination records.
Illustration:
Step 1: Open Tableau Step 2: Click "Connect to Data" Step 3: Choose your file (e.g., Excel) Step 4: Click "Open" β now your data is ready!
Mini summary: Connecting is how Tableau gets your data. It's the first step.
Definition: A bar chart uses rectangular bars to show values. The taller the bar, the bigger the number.
Why it is important: Bar charts are the easiest way to compare things.
Simple explanation: Like a race where each runner is a bar β the tallest bar wins.
Realβlife example: Compare sales of different products.
School example: Compare the number of students in each grade.
Home example: Compare how many hours you sleep each day.
Nigerian example: Compare the production of yams, cassava, and maize in different states.
Illustration:
π Apples ββββββββββββββββββββ 80 π Bananas ββββββββββββββββ 60 π₯ Mangoes ββββββββββ 40
Mini summary: Bar charts compare categories. Taller bar = larger number.
Definition: A line chart shows how something changes over time (days, months, years).
Why it is important: It helps us see trends β going up, going down, or staying the same.
Simple explanation: Like a rollercoaster track β the line goes up and down.
Realβlife example: Stock prices over a year.
School example: Your test scores over the school year.
Home example: The temperature outside each day for a week.
Nigerian example: Rainfall in Abuja from January to December.
Illustration:
Sales
|
60| *
50| * *
40| * *
30| * *
20|* *
10| *
+--------------
Jan Feb Mar Apr
Mini summary: Line charts show changes over time.
Definition: A filter is a tool that shows only the data you want and hides the rest.
Why it is important: Sometimes we only care about one region or one product.
Simple explanation: Like putting on sunglasses β you only see certain colours.
Realβlife example: A store owner filters to see only sales from Lagos.
School example: A teacher filters to see only students who scored above 80.
Home example: You filter your playlist to show only songs by your favourite artist.
Nigerian example: A farmer filters weather data to see only the rainy season.
Illustration:
All Data β Filter β Only what you need [π] [π] [π½] (just corn data)
Mini summary: Filters help you zoom in on specific data.
Definition: A dashboard is a page that holds many charts together, like a control panel.
Why it is important: You can see everything at once and make better decisions.
Simple explanation: Like a video game HUD that shows your health, score, and map all on one screen.
Realβlife example: A company dashboard shows sales, profit, and customer feedback.
School example: A dashboard for a principal shows attendance, grades, and sports performance.
Home example: A dashboard of your chores: completed, pending, and rewards.
Nigerian example: A dashboard for a hospital shows number of patients, beds available, and medicines in stock.
Illustration:
+-------------------------------------------------+ | π DASHBOARD | | +------------+ +------------+ | | | Bar Chart | | Line Chart | | | | Sales by | | Sales over | | | | Product | | Time | | | +------------+ +------------+ | | +------------+ | | | Map | | | | Sales by | | | | Region | | | +------------+ | +-------------------------------------------------+
Mini summary: A dashboard combines many charts on one page.
Definition: In Tableau, you drag fields from the left and drop them onto shelves (like Rows, Columns, Marks) to build a chart.
Why it is important: It is the main way you create visualisations β very easy and fun.
Simple explanation: Like picking a toy and putting it on a shelf. You choose dimensions and measures and drop them where they belong.
Realβlife example: Drag "Product" to Columns and "Sales" to Rows to get a bar chart.
School example: Drag "Student" to Rows and "Score" to Columns.
Home example: Drag "Day" to Columns and "Hours of TV" to Rows.
Nigerian example: Drag "State" to Columns and "Population" to Rows.
Illustration:
[Product] β Drag to Columns [Sales] β Drag to Rows Result: Bar chart appears!
Mini summary: Drag and drop is how you tell Tableau what to draw.
Definition: The Marks card is a control that lets you change the colour, size, shape, and label of your chart.
Why it is important: It makes your charts beautiful and easier to understand.
Simple explanation: Like choosing a paintbrush and colours for your drawing.
Realβlife example: Colour bars by product category.
School example: Make bars blue for boys and pink for girls.
Home example: Change the size of dots based on how many hours you slept.
Nigerian example: Colour Nigerian states differently on a map.
Illustration:
Marks Card: [Colour] β Choose red, blue, green [Size] β Make bars thicker or thinner [Label] β Show numbers on the bars
Mini summary: Marks card lets you style your chart.
Definition: A story in Tableau is a sequence of charts and dashboards that tell a story, like a slideshow.
Why it is important: It guides the viewer through your findings step by step.
Simple explanation: Like a comic book β each page shows a different part of the adventure.
Realβlife example: A business report that starts with sales, then profits, then future plans.
School example: A story about class performance: first overall, then by subject, then by gender.
Home example: A story about your week: Monday's activities, Tuesday's, etc.
Nigerian example: A story about crop production: planting, growing, harvesting, selling.
Illustration:
Story Point 1 β Story Point 2 β Story Point 3 [Sales Chart] [Profit Chart] [Future Plan]
Mini summary: Stories are like presentations made of charts.
Definition: You can share your Tableau work by exporting it as an image, PDF, or publishing it online.
Why it is important: So others can see your amazing charts and learn from them.
Simple explanation: Like showing your painting to your family.
Realβlife example: Email a dashboard to your manager.
School example: Print a chart for the class bulletin board.
Home example: Show your family the chart of your savings.
Nigerian example: A teacher shares a dashboard with the school board.
Illustration:
Tableau β Export β PDF / Image / Tableau Public Then you can share with anyone!
Mini summary: Sharing lets others see and learn from your work.
Definition: Data can be numbers (integers, decimals), text (strings), or dates.
Why it is important: Tableau needs to know the type to treat it correctly.
Simple explanation: Like sorting toys into boxes: numbers in one box, names in another, dates in another.
Realβlife example: "23" is a number, "John" is text, "2025-01-01" is a date.
School example: "Grade 5" is text; "80%" is a number.
Home example: "Sunday" is text; "7" is a number.
Nigerian example: "Lagos" is text; "15,000,000" is a number.
Illustration:
Data Types: π’ Number: 10, 3.14, 1000 π€ String: "Hello", "Nigeria" π Date: 2026-07-04
Mini summary: Know if your data is a number, word, or date β it helps Tableau.
Connect to Data
|
V
Drag Dimension to Columns
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V
Drag Measure to Rows
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V
Chart Appears!
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V
Customise with Marks Card
0:00 β Open Tableau 2:00 β Connect to data 4:00 β Drag first dimension 6:00 β Drag first measure 8:00 β Add filter 10:00 β Save your work
| Feature | Bar Chart | Line Chart |
|---|---|---|
| Best for | Comparing categories | Showing trends over time |
| Example | Sales by product | Sales by month |
| Axis | Categories on x-axis | Time on x-axis |
Well done! You have completed Module Three. You learned that data is information, and Tableau turns data into pictures. You now know the difference between dimensions and measures, and you can create bar charts, line charts, and dashboards. You also learned how to use filters, drag and drop, and even tell a story with your charts. Keep practising, and soon you will be a Tableau expert!
| Term | Definition |
|---|---|
| 1. Dimension | A. Shows change over time |
| 2. Measure | B. A collection of charts |
| 3. Bar Chart | C. Categories like "City" |
| 4. Line Chart | D. Numbers like "Sales" |
| 5. Dashboard | E. Compares categories with bars |
Answers: 1-C, 2-D, 3-E, 4-A, 5-B
Scenario: A school principal wants to see which grade has the highest average test score. She has data for Grade 4, 5, and 6. How would you use Tableau to help her? Describe the steps.
In groups of 3, collect data on favourite fruits from 10 classmates. Use Tableau to create a bar chart and present it to the class.
Use your weekly pocket money data (7 days) to create a line chart showing how much you spent each day.
Task: Create a dashboard that shows: (1) a bar chart of your class subjects and average scores, (2) a line chart of your scores over the last 5 tests, and (3) a filter to see only scores above 70.
Download a sample dataset (e.g., Superstore) and create a bar chart of sales by category, a line chart of sales by month, and a dashboard combining both.
Use a map in Tableau to show sales by state in Nigeria. Add a filter to see only states with sales above β¦1,000,000.
Fill-in-the-blank: 1. information, 2. charts, 3. Dimensions, measures, 4. filter, 5. dashboard.
True/False: 1F, 2F, 3T, 4T, 5F.
MCQs: 1B, 2C, 3B, 4B, 5B, 6D, 7D, 8A, 9B, 10C, 11C, 12A, 13B, 14B, 15A.
In the next module, we will dive deeper into Tableau calculations, learn about table calculations, and create more advanced charts like scatter plots and histograms. Make sure you are comfortable with drag and drop, filters, and dashboards. Practice with different datasets!
See you in Module 4!
Welcome, data explorer! In this module, we will learn how to take all the charts and graphs we have made and put them together into one big, beautiful picture called a dashboard. We will also learn how to make a story that shows people what the data is saying.
Think of a dashboard like a car dashboard β it shows you everything you need to know at a glance: speed, fuel, temperature. Our Tableau dashboard will show numbers, trends, and important facts all in one place.
By the end of this module, you will be able to:
Amina is a student in Lagos. Her teacher asked the class to find out which fruits are most popular in their school. Amina collected data from 100 students. She made a bar chart for mangoes, a pie chart for oranges, and a line chart showing how fruit sales change each month.
But when she showed her teacher, the teacher said, βAmina, you have many nice charts, but I have to open them one by one. Can you put them all on one page so I can see everything together?β
That is exactly what a dashboard does! Amina used Tableau to put all her charts on one page, added a title, and even a filter so you can see only the fruits you like. Her teacher was very happy. Amina became the βdata storytellerβ of her class.
Definition: A dashboard is a single page that shows many charts, numbers, and maps together.
Why important: It helps us see the whole picture quickly, without clicking around.
Simple explanation: Imagine you have a poster with all your best drawings. Your friends can see everything at once. A dashboard is like that poster for data.
Real-life example: In a hospital, a dashboard shows how many patients are waiting, how many beds are free, and which doctors are on duty β all on one screen.
School example: Your teacher has a dashboard that shows how many students passed each subject.
Home example: A family dashboard could show the weather, the calendar, and a to-do list.
Nigerian example: A market seller can have a dashboard showing daily sales of yam, rice, and beans, and also the total money earned.
π DASHBOARD = ONE PAGE WITH MANY CHARTS +-----------------------+ | TITLE: MY FRUIT DATA | | [Bar chart] [Pie] | | [Line chart] [Map] | | Filter: All Fruits | +-----------------------+
Mini summary: A dashboard puts many charts on one page so we can see everything at once.
Definition: We use a dashboard to monitor, compare, and decide quickly.
Why important: It saves time and helps us spot problems fast.
Simple explanation: If you have a big puzzle, putting all the pieces together shows the full picture. A dashboard does the same for numbers.
Real-life example: Air traffic controllers use a dashboard to see all planes in the sky.
School example: A principal uses a dashboard to see attendance for every class.
Home example: Parents can have a dashboard for chores β who did what.
Nigerian example: A bus company in Abuja can track all its buses on one dashboard β speed, location, and passenger count.
WHY DASHBOARD? +-------------------+ | 1. See all data | | 2. Compare easily | | 3. Make decisions | | 4. Save time | +-------------------+
Mini summary: Dashboards help us make better decisions faster.
Definition: A dashboard has worksheets (charts), objects (text, images), and filters.
Why important: Knowing the parts helps you build your dashboard like building with Lego blocks.
Simple explanation: Think of a dashboard as a pizza. The base is the page, the toppings are the charts, and the cheese is the filters that make it all stick together.
Real-life example: A sports dashboard has a scoreboard (text), a player stats chart, and a filter to choose teams.
School example: A dashboard for a science fair can have a chart for each experiment.
Home example: A chore dashboard has a list (text), a chart of who did most chores, and a filter for the week.
Nigerian example: A farm dashboard has a map of fields, a chart of crop growth, and a filter for each crop type.
DASHBOARD PARTS +---------------------------+ | TITLE | | +------+ +--------+ | | |Chart1| | Chart2 | | | +------+ +--------+ | | +--------+ | | | Filter | | | +--------+ | +---------------------------+
Mini summary: A dashboard is made of charts, text, and filters arranged on one page.
Definition: We use the Dashboard tab in Tableau to drag and drop our sheets (charts) onto a blank page.
Why important: This is how we build the dashboard step by step.
Simple explanation: It is like arranging pictures in a photo album. You pick the pictures you like and place them where you want.
Real-life example: A chef arranges different dishes on a buffet table.
School example: You arrange your best drawings on a poster for parentsβ day.
Home example: You arrange family photos on a wall.
Nigerian example: A shop owner arranges different products on shelves to show customers.
STEPS TO CREATE DASHBOARD 1. Click "New Dashboard" 2. Drag your sheets (charts) into the dashboard 3. Arrange them nicely 4. Add a title 5. Add a filter 6. Publish or save
Mini summary: To build a dashboard, drag your charts onto the dashboard page and arrange them.
Definition: A filter is a tool that lets you choose what data you want to see, like a spotlight.
Why important: Filters help you focus on one part of the data, like only one fruit or one region.
Simple explanation: Imagine you have a box of crayons. A filter is like picking only the red crayons to draw.
Real-life example: On a shopping website, you filter by size or colour.
School example: Filter by class to see only grade 5 results.
Home example: Filter by month to see expenses for January.
Nigerian example: Filter by state to see only Lagos sales.
FILTER EXAMPLE +-----------------------+ | Fruit: [Mango βΌ] | | +------+ +--------+ | | | Bar | | Pie | | | +------+ +--------+ | +-----------------------+ When you select Mango, both charts show mango data.
Mini summary: Filters let you zoom in on specific data, like choosing one colour from a rainbow.
Definition: You can add text boxes (for titles or explanations) and images (like logos) to your dashboard.
Why important: Text and images make your dashboard clear and attractive.
Simple explanation: Like adding captions to your drawings so people understand them better.
Real-life example: A news dashboard has the news channel logo and a headline.
School example: A project dashboard has the studentβs name and a school logo.
Home example: A family dashboard has a family photo and a βWelcomeβ text.
Nigerian example: A dashboard for a local business can have the business name and a picture of the shop.
ADD TEXT +-----------------------+ | π« MY SCHOOL DATA | | [Chart1] [Chart2] | | Made by: Amina | +-----------------------+
Mini summary: Text and images make your dashboard more friendly and informative.
Definition: Interactive means the user can click, filter, or hover to see more details.
Why important: It makes exploring data fun and helps people discover stories themselves.
Simple explanation: Like a video game where you press buttons to see different things.
Real-life example: On a map dashboard, you can click a city to see its population.
School example: Click a subject to see which students passed.
Home example: Click a day to see the weather details.
Nigerian example: Click a state to see its main crops.
INTERACTIVE DASHBOARD [Click on a bar] β shows details [Hover over a pie] β shows percentage [Filter dropdown] β changes all charts
Mini summary: Interactive dashboards let users play with the data.
Definition: A story is a series of dashboards or sheets that tell a narrative, like a slide show.
Why important: Stories guide people step by step through the data, from question to answer.
Simple explanation: Like a comic book β each page shows a new part of the adventure.
Real-life example: A company uses a story to show sales growth over 5 years, page by page.
School example: A story about how reading scores improved after a new library.
Home example: A story about saving money for a vacation β month by month.
Nigerian example: A story about how a farmerβs harvest increased after using better seeds.
STORY PAGES Page 1: Introduction Page 2: First chart (Sales) Page 3: Second chart (Regions) Page 4: Conclusion
Mini summary: A story is a sequence of dashboards that tells a data tale.
Definition: Click the βStoryβ tab, then drag your dashboards or sheets into the story, one by one.
Why important: This is how we build our data narrative.
Simple explanation: Like making a slide show with your favourite pictures.
Real-life example: A travel agent creates a story with a map, then prices, then photos of hotels.
School example: A science story: first hypothesis, then experiment, then results.
Home example: A story about your petβs growth: baby, toddler, adult.
Nigerian example: A story about a small business: starting, growing, and becoming popular.
STORY BUILDING 1. New Story 2. Drag Dashboard 1 (Intro) 3. Drag Dashboard 2 (Data) 4. Drag Dashboard 3 (Conclusion)
Mini summary: Build a story by adding dashboards in order, like pages in a book.
Definition: You can share by publishing to Tableau Public, saving as a file, or taking a screenshot.
Why important: Sharing helps others learn from your data.
Simple explanation: Like showing your art to friends and family.
Real-life example: A scientist shares a dashboard about climate change with the world.
School example: You share your project dashboard with your classmates.
Home example: You share your chore dashboard with your siblings.
Nigerian example: A local government shares a dashboard of school feeding program results.
SHARE OPTIONS +------------------------+ | 1. Tableau Public | | 2. PDF / Image | | 3. Email link | | 4. Embed in website | +------------------------+
Mini summary: Sharing your dashboard spreads knowledge and helps others.
Definition: Best practices are rules to make your dashboard clear and useful.
Why important: A messy dashboard confuses people; a clean dashboard helps them.
Simple explanation: Like cleaning your room β everything has a place.
Real-life example: A weather dashboard only shows temperature, rain, and wind β not extra noise.
School example: A class dashboard shows only attendance, grades, and homework.
Home example: A family dashboard shows only the schedule and shopping list.
Nigerian example: A market dashboard shows only top-selling items and total sales.
BEST PRACTICES - Use few colours - Big, clear fonts - Add titles - Donβt crowd - Use filters wisely
Mini summary: Keep your dashboard simple and easy to read.
Definition: Choose a size (like A4 or widescreen) and arrange charts in a grid.
Why important: Good layout makes your dashboard look professional.
Simple explanation: Like arranging books on a shelf β you put big ones at the bottom.
Real-life example: A stock market dashboard has large line charts at the top.
School example: A timetable dashboard has class names in rows.
Home example: A menu dashboard has breakfast, lunch, dinner in columns.
Nigerian example: A bus dashboard has route names on the left, times on the right.
LAYOUT EXAMPLE (Grid) +--------+--------+ | Chart1 | Chart2 | +--------+--------+ | Chart3 | Filter | +--------+--------+
Mini summary: Arrange charts in a neat grid for a clean look.
+--------------------------------------------------+ | π MY SPORTS DASHBOARD | | +----------------+ +-------------------------+ | | | [Bar chart] | | [Pie chart] | | | | Goals per player| | Win percentage | | | +----------------+ +-------------------------+ | | +----------------+ +-------------------------+ | | | [Line chart] | | [Filter: Team βΌ] | | | | Points over time| | | | | +----------------+ +-------------------------+ | +--------------------------------------------------+
[Start] β [Page 1: Intro] β [Page 2: Data] β [Page 3: Conclusion] β [End]
| Feature | Dashboard | Story |
|---|---|---|
| Purpose | Show all at once | Guide step by step |
| Pages | One page | Multiple pages |
| Interactivity | High (filters) | Medium (navigation) |
| Best for | Monitoring | Presenting |
Congratulations! You have learned how to create powerful dashboards and stories in Tableau. You now know how to combine charts, add filters, arrange layouts, and share your work. Dashboards help us see the big picture, and stories help us explain it to others. Remember to keep your designs clean and your audience in mind. With these skills, you are well on your way to becoming a Tableau expert!
Match the term on the left with the correct description on the right.
| Term | Description |
|---|---|
| 1. Dashboard | A. A tool to choose data |
| 2. Filter | B. A series of pages that tell a story |
| 3. Story | C. One page with many charts |
| 4. Layout | D. How items are arranged |
Answers: 1-C, 2-A, 3-B, 4-D
Scenario: You are a data analyst for a school. The principal wants to see attendance, grades, and library visits on one page.
In groups of 3, collect data about your favourite hobbies (e.g., sports, reading). Each student creates one chart. Then together, build a dashboard combining all three charts. Present it to the class.
Create a dashboard about your daily routine (wake-up time, study time, play time). Use at least two charts and one filter. Save and share with a partner.
Project: Create a dashboard showing the favourite foods of your class. Collect data, make at least three charts (bar, pie, line), combine them into a dashboard, add a filter for βclass gradeβ, and add a title. Present your dashboard to the class.
Using Tableau Public, build a dashboard from the βSuperstoreβ sample data. Include a map, a bar chart, and a line chart. Add a filter for βRegionβ. Publish it and share the link.
Create a story with 4 pages using your dashboard from the practical assignment. Add captions and a conclusion. Share the story link with your teacher.
(Answers provided within the multiple choice and matching sections above.)
In the next module, we will dive deeper into advanced analytics. You will learn how to use calculations, parameters, and forecasting. Be sure to practice building dashboards and stories, as these skills will be the foundation for advanced work. Get ready to become a true Tableau wizard!
End of Module 5 Β· Keep exploring data!
Welcome, data superstar! In this module, we will learn how to make our data even smarter. We will use calculations (like adding or multiplying numbers), parameters (like a slider that changes numbers), and forecasting (like predicting the future).
Imagine you have a magic calculator that can not only add numbers but also guess what might happen next week. That is what we will do with Tableau!
By the end of this module, you will be able to:
Chidi is a smart boy in Enugu. He sells lemonade every Saturday. He keeps a record of how many cups he sells and how much money he makes.
One day, he thought, βI want to know my total money for the whole month without adding each day manually.β So he used a calculation to add all his daily sales.
Then he thought, βWhat if I raise my price by 50 naira? How much more money will I make?β He used a parameter to change the price and see the result instantly.
Finally, he wondered, βHow many cups will I sell next Saturday?β He used forecasting to guess based on past data.
Chidi became the lemonade king of his street!
Definition: A calculation is a math operation you do on your data, like addition, subtraction, multiplication, or division.
Why important: Calculations help you get new numbers from existing data.
Simple explanation: If you have βnumber of applesβ and βprice per appleβ, you can multiply to get βtotal costβ.
Real-life example: A shopkeeper calculates total sales by adding all items sold.
School example: Your teacher calculates your total score by adding marks from all subjects.
Home example: You calculate your pocket money by adding what you get each week.
Nigerian example: A farmer calculates total harvest by adding yams from each field.
CALCULATION EXAMPLE Sales (cups) Γ Price (naira) = Total Money 20 cups Γ 100 naira = 2000 naira
Mini summary: Calculations turn raw numbers into useful information.
Definition: In Tableau, you write a formula using fields and math symbols (+, -, *, /).
Why important: You can create new fields that don't exist in your original data.
Simple explanation: Like making a new recipe by mixing ingredients.
Real-life example: A store creates a βprofitβ field by subtracting cost from sales.
School example: Create a βtotal marksβ field by adding all subject marks.
Home example: Create a βtotal choresβ field by adding chores done each day.
Nigerian example: Create a βtotal rainfallβ field by adding daily rainfall amounts.
STEPS TO CREATE CALCULATION 1. Right-click in the Data pane. 2. Choose βCreate Calculated Fieldβ. 3. Give it a name (e.g., βTotal Profitβ). 4. Write the formula: [Sales] - [Cost]. 5. Click OK.
Mini summary: You can create new data fields by writing formulas in Tableau.
Definition: Row-level calculations work on each row of data. Aggregate calculations work on groups of rows (like sum or average).
Why important: Different situations need different types.
Simple explanation: Row-level is like counting each apple separately. Aggregate is like counting all apples in a basket.
Real-life example: Row-level: price of each item. Aggregate: total price of all items.
School example: Row-level: score for each test. Aggregate: average score.
Home example: Row-level: temperature each hour. Aggregate: average temperature for the day.
Nigerian example: Row-level: rainfall each day. Aggregate: total rainfall for the month.
ROW-LEVEL vs AGGREGATE +----------------------+------------------------+ | Row-level (each row) | Aggregate (group) | | Price per item | Sum of all prices | | Score per student | Average score | +----------------------+------------------------+
Mini summary: Row-level works on single rows, aggregate works on groups.
Definition: SUM adds numbers, AVG finds the average, MIN finds the smallest, MAX finds the largest.
Why important: These are the most common calculations.
Simple explanation: SUM = total, AVG = middle, MIN = smallest, MAX = largest.
Real-life example: SUM of all sales, AVG of customer ratings.
School example: SUM of marks, AVG score, MIN score, MAX score.
Home example: SUM of expenses, AVG daily temperature.
Nigerian example: SUM of harvest from all farms.
EXAMPLES SUM([Sales]) = total sales AVG([Sales]) = average sale MIN([Sales]) = smallest sale MAX([Sales]) = largest sale
Mini summary: SUM, AVG, MIN, MAX help you summarise data.
Definition: A parameter is a variable that the user can change, like a slider or a dropdown.
Why important: Parameters let users explore βwhat ifβ scenarios.
Simple explanation: Like a volume knob β you turn it and the sound changes.
Real-life example: A price slider on a shopping website.
School example: A parameter to change the passing mark.
Home example: A parameter to change the dinner time.
Nigerian example: A parameter to change the exchange rate for dollars to naira.
PARAMETER EXAMPLE [Price Increase] = 10% (user can change) New Price = Old Price * (1 + [Price Increase])
Mini summary: Parameters let users change values and see results instantly.
Definition: In Tableau, you create a parameter by right-clicking in the Data pane and choosing βCreate Parameterβ.
Why important: You can use parameters in calculations, filters, and dashboards.
Simple explanation: Like setting up a dial that users can turn.
Real-life example: A restaurant creates a parameter for tip percentage.
School example: A parameter for the number of weeks in a term.
Home example: A parameter for the number of family members.
Nigerian example: A parameter for the price of a bag of rice.
STEPS TO CREATE PARAMETER 1. Right-click in Data pane β Create Parameter. 2. Name it (e.g., βDiscountβ). 3. Choose data type (e.g., Float, Integer). 4. Set value range (e.g., 0 to 100). 5. Click OK.
Mini summary: Creating a parameter is easy and makes your dashboard interactive.
Definition: You can use a parameter inside a calculation to create dynamic values.
Why important: It makes your analysis flexible.
Simple explanation: You write a formula that includes the parameter, and when the user changes the parameter, the result changes.
Real-life example: Sales * (1 + [Commission Rate]).
School example: Score * [Weighting Factor].
Home example: Budget * [Emergency Factor].
Nigerian example: Harvest * [Storage Loss Percentage].
CALCULATION WITH PARAMETER [Sales] * [Discount] (Discount is a parameter) If Discount = 0.1, result = Sales * 0.9 (10% off) If Discount = 0.2, result = Sales * 0.8 (20% off)
Mini summary: Parameters in calculations let you test different scenarios.
Definition: Forecasting is predicting future values based on past data.
Why important: It helps us plan for the future.
Simple explanation: Like guessing the weather tomorrow based on past weather.
Real-life example: A shop predicts next month's sales to order stock.
School example: Predicting next year's student population.
Home example: Predicting next month's electricity bill.
Nigerian example: Predicting next season's crop yield.
FORECAST EXAMPLE Past Sales: 100, 120, 140, 160 Forecast for next month: 180 (if trend continues)
Mini summary: Forecasting uses past data to guess the future.
Definition: In Tableau, you can add a forecast by right-clicking on a chart and choosing βForecastβ.
Why important: It's easy and gives you a visual prediction.
Simple explanation: You click a button, and Tableau draws a future line.
Real-life example: Forecasting sales for the next quarter.
School example: Forecasting how many students will pass next year.
Home example: Forecasting when you will finish your savings.
Nigerian example: Forecasting rainfall for the next planting season.
STEPS TO ADD FORECAST 1. Create a line chart with time on the x-axis. 2. Right-click on the chart. 3. Choose βForecastβ. 4. Tableau will add a forecast line (often dashed).
Mini summary: Tableau can add a forecast to your chart with a few clicks.
Definition: Tableau uses models like Exponential Smoothing to make forecasts.
Why important: The model affects how accurate the forecast is.
Simple explanation: Think of it like choosing a recipe β different recipes give different cakes.
Real-life example: A store uses a model that gives more weight to recent sales.
School example: A model that predicts attendance based on last 5 years.
Home example: A model that predicts grocery spending based on last 3 months.
Nigerian example: A model that predicts harvest based on the last 5 seasons.
FORECAST MODEL TYPES +------------------------+---------------------------+ | Simple Exponential | Smoothing (no trend) | | Double Exponential | Smoothing with trend | | Triple Exponential | Smoothing with trend & season | +------------------------+---------------------------+
Mini summary: Tableau has different forecast models for different data patterns.
Definition: Accuracy tells us how close the forecast is to the real values.
Why important: We need to know if we can trust the forecast.
Simple explanation: If you guess the weather and it rains when you said sunny, your guess was not accurate.
Real-life example: A store checks if their sales forecast was close to actual sales.
School example: Check if the predicted number of students matches actual enrolment.
Home example: Check if predicted electricity bill matches actual bill.
Nigerian example: Check if predicted harvest matches actual harvest.
ACCURACY MEASURES - MAPE: Mean Absolute Percentage Error (lower is better) - RMSE: Root Mean Square Error (lower is better)
Mini summary: We check forecast accuracy to see if we can believe the prediction.
Definition: You can use all three together in one dashboard for powerful analysis.
Why important: This gives you a complete tool for exploring data.
Simple explanation: Like having a Swiss Army knife β many tools in one.
Real-life example: A dashboard shows sales, allows changing discount (parameter), and forecasts future sales.
School example: A dashboard shows scores, allows changing passing mark (parameter), and predicts next year's scores.
Home example: A dashboard shows expenses, allows changing budget (parameter), and forecasts future expenses.
Nigerian example: A dashboard shows farm data, allows changing price (parameter), and forecasts next harvest.
COMBINED DASHBOARD +--------------------------------------+ | Sales Data | | +--------+ +--------+ +------------+ | | | Chart | | Filter | | Parameter | | | +--------+ +--------+ +------------+ | | Forecast: future sales | +--------------------------------------+
Mini summary: Combining calculations, parameters, and forecasting makes a super dashboard.
Definition: Forecasting helps in agriculture, business, and government.
Why important: It helps people make better decisions.
Simple explanation: Like looking at a map before a journey.
Real-life example: A farmer forecasts rainfall to decide when to plant.
School example: A school forecasts enrolment to plan for new teachers.
Home example: A family forecasts expenses to save money.
Nigerian example: The government forecasts tax revenue to plan the budget.
NIGERIAN FORECAST USES - Farming: predict harvest - Business: predict sales - Transport: predict passenger numbers - Health: predict patient numbers
Mini summary: Forecasting is used everywhere in Nigeria to plan ahead.
Definition: You can share your dashboard with calculations, parameters, and forecasts.
Why important: Others can benefit from your smart analysis.
Simple explanation: Like sharing your secret recipe with friends.
Real-life example: A business shares its sales dashboard with managers.
School example: A teacher shares a dashboard with students.
Home example: Share your family budget dashboard with parents.
Nigerian example: A farmer shares a dashboard with other farmers.
SHARING OPTIONS - Tableau Public - Email - PDF - Embedded in a website
Mini summary: Share your smart dashboards to help others make decisions.
Data (Sales, Cost)
|
V
Calculation: Sales - Cost
|
V
New Field: Profit
Parameter: Discount (0 to 1)
|
V
Calculation: Sales * (1 - Discount)
|
V
Result: Discounted Sales
Past Data (2019-2024)
|
V
Forecast Model (Exponential Smoothing)
|
V
Future Prediction (2025-2026)
| Feature | Calculation | Parameter | Forecast |
|---|---|---|---|
| Purpose | Create new data | Allow user input | Predict future |
| User changes? | No | Yes | No |
| Example | Profit = Sales - Cost | Discount rate | Next month sales |
| Type | Works on | Example |
|---|---|---|
| Row-level | Each row individually | Price per item |
| Aggregate | Group of rows | Total price |
Excellent work! You have learned three powerful tools: calculations, parameters, and forecasting. Calculations help you create new numbers from your data. Parameters let you and others change values to see different results. Forecasting helps you predict the future based on past data. By combining these tools, you can build interactive and smart dashboards that help people make better decisions. Now you are ready to use these skills in your projects and even in real life!
Match the term with its description.
| Term | Description |
|---|---|
| 1. Calculation | A. Predicts future values |
| 2. Parameter | B. Math operation on data |
| 3. Forecast | C. User-changeable value |
| 4. Aggregate | D. Summary of multiple rows |
Answers: 1-B, 2-C, 3-A, 4-D
Scenario: You are a data analyst for a supermarket. The manager wants to see monthly sales, allow a discount (parameter), and predict next month's sales.
In groups of 4, collect data on daily temperatures for the last 2 weeks. Use Tableau to calculate the average temperature, add a parameter to increase or decrease the temperature by 2 degrees, and forecast the temperature for the next week. Present your findings.
Create a dashboard using your own data (e.g., your weekly study hours). Include a calculation (total hours), a parameter (goal hours), and a forecast for next week's study hours.
Project: Create a dashboard that shows monthly sales of a small shop. Include a calculation for profit, a parameter for discount, and a forecast for the next 3 months. Present your dashboard to the class.
Using Tableau Public, create a dashboard with the following:
Publish and share the link.
Create a story with 3 pages: Page 1 shows sales data, Page 2 shows calculations and parameters, Page 3 shows the forecast. Add a caption to each page explaining what you see. Share the story link.
(Answers provided within the multiple choice and matching sections above.)
In the next module, we will explore advanced visualisations like heat maps, tree maps, and box plots. We will also learn how to combine multiple data sources. Make sure you are comfortable with calculations, parameters, and forecasting because we will use them in more advanced ways. Get ready to create stunning visual stories!
End of Module 6 Β· Keep making data smarter!
Welcome, data artist! In this module, we will learn how to create fancy charts that make our data look like a beautiful painting. We will use heat maps (like a temperature map), tree maps (like a family tree), and box plots (like a box that shows data spread).
We will also learn how to combine data from different sources, like mixing two colours to make a new one.
By the end, you will be able to create amazing and colourful charts that everyone will love to see!
By the end of this module, you will be able to:
Ada loves art. She has a gallery with many paintings. She wants to show which colours are most popular in her gallery.
She used a heat map to show where the most colourful paintings are. She used a tree map to show how many paintings are in each colour category (red, blue, green). And she used a box plot to show the range of prices for each colour.
She also combined data from her sales records and her visitor records to see which colours sell best.
Ada's gallery became the most popular in Lagos because she could show her art data in such a beautiful way!
Definition: A heat map uses colours to show values. Darker colours mean higher values, lighter colours mean lower values.
Why important: It helps you see patterns and hot spots quickly.
Simple explanation: Like a weather map where red means hot and blue means cold.
Real-life example: A map showing where most car accidents happen (red for high, green for low).
School example: A heat map showing which subjects students find hardest (red = difficult, green = easy).
Home example: A heat map of room temperatures (red = hot rooms, blue = cold rooms).
Nigerian example: A heat map of rainfall in different states (dark blue = heavy rain, light blue = little rain).
HEAT MAP EXAMPLE +----+----+----+----+ | 10 | 20 | 30 | 40 | (numbers) +----+----+----+----+ | π₯ | π§ | π¨ | π© | (colours) +----+----+----+----+ Red = highest, Green = lowest
Mini summary: Heat maps use colours to show values β darker = more, lighter = less.
Definition: In Tableau, you create a heat map by putting a field on Colour and another on Rows or Columns.
Why important: It's easy and shows patterns instantly.
Simple explanation: Like colouring a grid by number β high numbers get dark colours.
Real-life example: A store creates a heat map of sales by day and hour.
School example: A heat map of test scores by subject and student.
Home example: A heat map of chores done by family member and day.
Nigerian example: A heat map of harvest by region and crop.
STEPS TO CREATE HEAT MAP 1. Drag a dimension to Columns (e.g., Region). 2. Drag another dimension to Rows (e.g., Product). 3. Drag a measure to Colour (e.g., Sales). 4. Choose a colour palette.
Mini summary: Heat maps are easy to create in Tableau and show data patterns.
Definition: A tree map shows data as rectangles. Bigger rectangles mean bigger values.
Why important: It shows parts of a whole at a glance.
Simple explanation: Like a pizza cut into slices, but the slices are rectangles.
Real-life example: A tree map of a company's sales by product β the biggest rectangle is the top-selling product.
School example: A tree map of marks by subject β the biggest rectangle is the subject with the highest total marks.
Home example: A tree map of expenses β rent is the biggest rectangle.
Nigerian example: A tree map of crops by farm β maize takes the biggest rectangle.
TREE MAP EXAMPLE +------------------+---------+ | | | | MAIZE | RICE | | (biggest) | | +------------------+----+----+ | CASSAVA |YAM| | | | | | +-------------------+---+----+
Mini summary: Tree maps use rectangles to show values β bigger = more.
Definition: In Tableau, you create a tree map by selecting the Tree Map chart type.
Why important: It's a great way to show proportions.
Simple explanation: You choose the tree map icon, and Tableau does the rest.
Real-life example: A tree map of market share by brand.
School example: A tree map of library book categories.
Home example: A tree map of food items in your fridge.
Nigerian example: A tree map of jobs by sector (farming, trading, etc.).
STEPS TO CREATE TREE MAP 1. Choose a dimension (e.g., Category). 2. Choose a measure (e.g., Sales). 3. Click on the Tree Map chart type. 4. Drag a dimension to Colour if you want more detail.
Mini summary: Tree maps show parts of a whole with rectangles.
Definition: A box plot shows the spread of data. It shows the minimum, maximum, median, and quartiles.
Why important: It shows how data is distributed β are most values close or spread out?
Simple explanation: Like a box with a line in the middle. The box shows the middle 50% of data, and the whiskers show the rest.
Real-life example: A box plot of students' exam scores β shows the range and average.
School example: A box plot of heights in a class.
Home example: A box plot of daily temperatures for a month.
Nigerian example: A box plot of salaries in different professions.
BOX PLOT EXAMPLE +----+----+----+----+----+ | | | | | | | | | | | | | | | | | | | | | | | | +----+----+----+----+----+ Min Q1 Med Q3 Max (Q1 = 25th percentile, Q3 = 75th percentile)
Mini summary: Box plots show the spread and middle of data.
Definition: In Tableau, you create a box plot by using the βBox Plotβ chart type.
Why important: It's the best way to see outliers and distribution.
Simple explanation: You select the box plot icon, and Tableau draws the box and whiskers.
Real-life example: A box plot of customer ages in different regions.
School example: A box plot of test scores by grade.
Home example: A box plot of weekly allowance.
Nigerian example: A box plot of temperatures in different cities.
STEPS TO CREATE BOX PLOT 1. Drag a measure to Rows (e.g., Sales). 2. Drag a dimension to Columns (e.g., Region). 3. Change the chart type to βBox Plotβ. 4. Optionally, add more dimensions to Colour.
Mini summary: Box plots are easy to create and show data distribution.
Definition: Quartiles divide data into four equal parts. Outliers are values that are far from the rest.
Why important: They help us understand the spread and find unusual data.
Simple explanation: Quartiles are like cutting a cake into four equal pieces. Outliers are like a very big or very small piece.
Real-life example: A box plot of house prices β outliers are very expensive or very cheap houses.
School example: A box plot of test scores β outliers are very high or very low scores.
Home example: A box plot of daily steps β outliers are days you walked very little or very much.
Nigerian example: A box plot of business profits β outliers are businesses that made very high or very low profit.
QUARTILES +----+----+----+----+ | Q1 | Q2 | Q3 | Q4 | (each 25%) +----+----+----+----+ Outliers are far from Q1 or Q3.
Mini summary: Quartiles split data into four parts; outliers are far from the middle.
Definition: Different charts are good for different types of data.
Why important: Choosing the right chart makes your data easy to understand.
Simple explanation: Like choosing the right tool for a job β you wouldn't use a hammer to paint a picture.
Real-life example: Use a bar chart for comparing categories, a line chart for trends, a heat map for patterns.
School example: Use a bar chart for comparing marks in subjects.
Home example: Use a pie chart for showing expenses by category.
Nigerian example: Use a tree map for showing crops by farm.
CHART SELECTION GUIDE +----------------+-------------------+ | Data type | Best chart | +----------------+-------------------+ | Comparison | Bar chart | | Trend | Line chart | | Proportion | Pie / Tree map | | Pattern | Heat map | | Distribution | Box plot | +----------------+-------------------+
Mini summary: Pick the chart that best shows your data story.
Definition: Combining data means bringing together data from different files or databases.
Why important: It gives you a fuller picture.
Simple explanation: Like mixing ingredients to make a cake β each ingredient alone is good, but together they are better.
Real-life example: A store combines sales data and customer feedback data.
School example: A school combines student grades and attendance data.
Home example: A family combines income and expense data.
Nigerian example: A farm combines weather data and harvest data.
COMBINING DATA Data Source 1 (Sales) + Data Source 2 (Customer Info) = Full Picture
Mini summary: Combining data gives you more insights.
Definition: A join is how you combine two tables of data. Types: Inner, Left, Right, and Full Outer.
Why important: Different joins show different parts of the data.
Simple explanation: Like holding two puzzle pieces together β you can hold them in different ways.
Real-life example: Inner join shows only rows that match in both tables.
School example: Left join shows all students and their grades if they have any.
Home example: Right join shows all expenses and the person who paid for them.
Nigerian example: Full outer join shows all farmers and all crops, even if no relation.
JOIN TYPES +------------------+----------------------+ | Join Type | What it shows | +------------------+----------------------+ | Inner | Only matching rows | | Left | All left + matching | | Right | All right + matching | | Full Outer | All rows from both | +------------------+----------------------+
Mini summary: Joins combine data in different ways.
Definition: In Tableau, you combine data by dragging tables to the canvas and choosing a join type.
Why important: It's easy and visual.
Simple explanation: You drag and drop tables like building blocks.
Real-life example: A store combines orders and customers by Customer ID.
School example: A school combines students and classes by Class ID.
Home example: A family combines expenses and categories by Category ID.
Nigerian example: A farm combines fields and crops by Field ID.
STEPS TO COMBINE DATA 1. Connect to your first data source. 2. Drag the second data source to the canvas. 3. Choose a join type (e.g., Inner). 4. Select the fields to join on (e.g., ID).
Mini summary: Combining data in Tableau is a visual drag-and-drop process.
Definition: Data blending is like a join, but it works on aggregated data from different sources.
Why important: It's useful when you can't do a direct join.
Simple explanation: Like mixing two different paints to get a new colour.
Real-life example: A store blends sales data from a database with exchange rates from a website.
School example: A school blends student data from a spreadsheet with library data from another system.
Home example: A family blends bank account data with expense tracker data.
Nigerian example: A farm blends weather data from a website with harvest data from a spreadsheet.
DATA BLENDING Primary Data Source + Secondary Data Source = Blended Data (Aggregated) (Aggregated)
Mini summary: Data blending combines data from different sources at an aggregated level.
Definition: Best practices are rules to follow when combining data.
Why important: They ensure your analysis is correct.
Simple explanation: Like following a recipe to make sure the cake tastes good.
Real-life example: Always check that the fields you join on are the same type (e.g., both are numbers).
School example: Make sure student IDs are the same format in both tables.
Home example: Make sure dates are in the same format.
Nigerian example: Make sure state names are spelled the same way.
BEST PRACTICES - Use consistent field names. - Use the same data types. - Test your joins with small data first. - Understand the meaning of each join type.
Mini summary: Follow best practices to combine data correctly.
+---------+----+----+----+----+ | Product | Mon | Tue | Wed | Thu | +---------+----+----+----+----+ | Apples | 10 | 20 | 30 | 40 | (values) | Oranges | 15 | 25 | 35 | 45 | +---------+----+----+----+----+ Colour scale: π₯ π§ π¨ π©
+------------------+---------+ | | | | MAIZE | RICE | | (biggest) | | +------------------+----+----+ | CASSAVA |YAM| | | | | | +-------------------+---+----+
+----+----+----+----+----+ | | | | | | | | | | | | | | | | | | | | | | | | +----+----+----+----+----+ Min Q1 Med Q3 Max
INNER JOIN +--------+ +--------+ | Table A | | Table B | +--------+ +--------+ | ID | A | | ID | B | | 1 | X | | 1 | Y | | 2 | Z | | 3 | W | +--------+ +--------+ Result: only ID 1 (matching)
| Feature | Heat Map | Tree Map | Box Plot |
|---|---|---|---|
| Shows | Patterns | Proportions | Distribution |
| Best for | Large datasets | Parts of a whole | Spread and outliers |
| Colour used | Yes | Yes (optional) | No |
| Feature | Join | Data Blending |
|---|---|---|
| Level | Row-level | Aggregate |
| Data source | Same or different | Different |
| Performance | Faster | Slower |
| Use when | Data is related | Data is independent |
Wonderful job! You have learned how to create three fancy charts: heat maps, tree maps, and box plots. You also learned how to combine data using joins and data blending.
Heat maps help you see patterns with colours. Tree maps show parts of a whole with rectangles. Box plots show the spread of data.
Combining data gives you a fuller picture. Now you can choose the right chart for your data and combine data from different sources to tell a complete story.
You are becoming a true data expert!
Match the chart with its description.
| Chart | Description |
|---|---|
| 1. Heat Map | A. Shows parts of a whole with rectangles |
| 2. Tree Map | B. Shows data spread with a box |
| 3. Box Plot | C. Uses colours to show values |
Answers: 1-C, 2-A, 3-B
Scenario: You are a data analyst for a supermarket. You have sales data and customer data.
In groups of 4, collect data on favourite fruits, sports, and colours. Create a heat map for one, a tree map for another, and a box plot for the third. Present your charts to the class.
Create a tree map of your monthly expenses. Use categories like food, transport, and fun. Share your tree map with a friend.
Project: Create a dashboard with three sheets: a heat map of sales by region and product, a tree map of sales by category, and a box plot of sales by region. Combine your data from at least two sources. Present your dashboard.
Using Tableau Public, create a heat map of daily temperatures for the last month. Then create a tree map of your expenses. Finally, create a box plot of your study hours. Publish your workbook.
Create a story with 4 pages: Page 1 β Heat map of sales, Page 2 β Tree map of products, Page 3 β Box plot of sales by region, Page 4 β Combined data story. Use data from at least two sources. Share the story link.
(Answers provided within the multiple choice and matching sections above.)
In the next module, we will dive into advanced analytics like creating calculated fields with logic (IF statements), using table calculations, and creating parameters for dynamic analysis. Make sure you are comfortable with the charts and joining techniques from this module. Get ready to become a Tableau master!
End of Module 7 Β· Keep creating beautiful charts!
Welcome, data wizard! In this module, we will learn how to make our data even smarter using IF statements (like making decisions), table calculations (like calculating across rows), and dynamic parameters (that change automatically).
Imagine you have a robot that can decide what to do based on rules. That's what IF statements do. Table calculations are like running a race β you look at the runner behind you and ahead of you. Dynamic parameters are like a thermostat that adjusts itself.
By the end, you will be able to create powerful formulas and dynamic dashboards!
By the end of this module, you will be able to:
Kofi is a smart boy in Accra. He has a robot that can sort his toys. The robot uses IF statements to decide: "If the toy is red, put it in the red box. If it's blue, put it in the blue box."
Kofi also uses table calculations to count his toys. He wants to know the running total of toys he collects each month. He uses a table calculation to add them up as he goes.
Finally, he uses dynamic parameters to change the sorting rule automatically. If he gets a new colour toy, the robot learns to sort it.
Kofi's robot became the smartest toy sorter in the neighbourhood!
Definition: An IF statement is a rule that says: "If this is true, then do this; otherwise, do that."
Why important: It helps you make decisions in your data.
Simple explanation: Like a fork in the road β if you go left, you see a lake; if you go right, you see a forest.
Real-life example: If sales are high, give a bonus; otherwise, give a small reward.
School example: If a student scores above 70, they pass; otherwise, they take a retest.
Home example: If it's raining, take an umbrella; otherwise, wear a cap.
Nigerian example: If a farmer has enough rain, the crop grows well; otherwise, they need irrigation.
IF STATEMENT EXAMPLE IF [Sales] > 1000 THEN "High" ELSE "Low" END
Mini summary: IF statements help you make decisions based on conditions.
Definition: In Tableau, you write an IF statement in a calculated field.
Why important: It allows you to create new categories or values.
Simple explanation: You write a formula that says: if this, then that.
Real-life example: Create a field called "Profit Category" β if profit > 500, "Good", else "OK".
School example: Create a field called "Grade" β if score > 80, "A", else "B".
Home example: Create a field called "Weather" β if temp > 30, "Hot", else "Cool".
Nigerian example: Create a field called "Harvest" β if yield > 1000, "Abundant", else "Average".
STEPS TO CREATE IF STATEMENT 1. Create a Calculated Field. 2. Write: IF [Field] > Value THEN "Result" ELSE "Other Result" END. 3. Click OK.
Mini summary: IF statements are easy to write and create new categories.
Definition: ELSE IF lets you check many conditions in one statement.
Why important: You can have more than two outcomes.
Simple explanation: Like a menu β if you want rice, choose rice; if you want beans, choose beans; otherwise, choose bread.
Real-life example: IF sales > 1000 THEN "High", ELSE IF sales > 500 THEN "Medium", ELSE "Low".
School example: IF score > 90 THEN "A", ELSE IF score > 70 THEN "B", ELSE "C".
Home example: IF temp > 35 THEN "Very Hot", ELSE IF temp > 25 THEN "Warm", ELSE "Cool".
Nigerian example: IF rainfall > 200 THEN "Flood", ELSE IF rainfall > 100 THEN "Normal", ELSE "Drought".
ELSE IF EXAMPLE IF [Sales] > 1000 THEN "High" ELSEIF [Sales] > 500 THEN "Medium" ELSE "Low" END
Mini summary: ELSE IF allows multiple conditions and outcomes.
Definition: Table calculations are calculations you apply to the table of data, like running totals or differences.
Why important: They help you see trends and patterns across rows.
Simple explanation: Like looking at a line of people and seeing how each person compares to the one before.
Real-life example: Running total of sales over months.
School example: Difference in marks between tests.
Home example: Running total of steps walked each day.
Nigerian example: Running total of harvest over seasons.
TABLE CALCULATION EXAMPLE Month Sales Running Total Jan 100 100 Feb 120 220 (100+120) Mar 130 350 (220+130)
Mini summary: Table calculations work on the data table to show summaries.
Definition: Common types: Running Total, Difference, Percent Difference, Rank, and Moving Average.
Why important: Each gives a different view of the data.
Simple explanation: Like different lenses on a camera β each shows something new.
Real-life example: Running Total shows cumulative sales. Difference shows change from previous month.
School example: Rank shows your position in class. Moving Average smooths out ups and downs.
Home example: Running Total of savings. Difference in daily expenses.
Nigerian example: Running Total of votes in an election. Difference in crop yield year over year.
TABLE CALCULATION TYPES +------------------+---------------------------+ | Type | What it does | +------------------+---------------------------+ | Running Total | Adds up as you go | | Difference | Previous - Current | | Percent Diff | Percentage change | | Rank | Orders from high to low | | Moving Average | Average of last few rows | +------------------+---------------------------+
Mini summary: Table calculations come in different types for different insights.
Definition: You add a table calculation by right-clicking on a measure and choosing "Add Table Calculation".
Why important: It's easy and you can choose the type.
Simple explanation: Like choosing a tool from a toolbox.
Real-life example: Add a Running Total to a sales line chart.
School example: Add a Rank to student scores.
Home example: Add a Difference to daily temperature.
Nigerian example: Add a Moving Average to monthly rainfall.
STEPS TO ADD TABLE CALCULATION 1. Right-click on the measure in the view. 2. Choose "Add Table Calculation". 3. Select the type (e.g., Running Total). 4. Choose the direction (e.g., Across or Down). 5. Click OK.
Mini summary: Adding a table calculation is a few clicks away.
Definition: Direction tells Tableau how to compute β across rows, down columns, or by pane.
Why important: It affects the result.
Simple explanation: Like reading a book β left to right or top to bottom.
Real-life example: Across β sales by month. Down β sales by product.
School example: Across β scores by subject. Down β scores by student.
Home example: Across β expenses by day. Down β expenses by category.
Nigerian example: Across β harvest by season. Down β harvest by crop.
DIRECTION EXAMPLE +--------+-------+-------+-------+ | | Jan | Feb | Mar | (Across) +--------+-------+-------+-------+ | Sales | 100 | 120 | 130 | | Profit | 20 | 25 | 30 | (Down) +--------+-------+-------+-------+
Mini summary: Direction tells Tableau how to compute the calculation.
Definition: A dynamic parameter is a parameter that changes automatically based on a field or calculation.
Why important: It makes your dashboard smarter and more responsive.
Simple explanation: Like a thermostat that adjusts the temperature automatically.
Real-life example: A parameter that sets the discount based on the total sales.
School example: A parameter that sets the passing mark based on the average score.
Home example: A parameter that sets the budget based on last month's expenses.
Nigerian example: A parameter that sets the price of rice based on the harvest.
DYNAMIC PARAMETER IDEA Parameter: Discount = IF [Sales] > 1000 THEN 0.1 ELSE 0.05 (The discount changes automatically)
Mini summary: Dynamic parameters change automatically based on data.
Definition: You create a parameter and then use a calculation to set its value.
Why important: It automates decision-making.
Simple explanation: You set up a rule that updates the parameter.
Real-life example: Parameter = Running Total of Sales.
School example: Parameter = Average Score.
Home example: Parameter = Total Expenses.
Nigerian example: Parameter = Total Harvest.
STEPS TO CREATE DYNAMIC PARAMETER 1. Create a parameter (e.g., "Dynamic Discount"). 2. Create a calculation that uses the parameter. 3. Use a table calculation or IF statement to set the parameter value. 4. Note: In Tableau, parameters are not fully dynamic but you can use workarounds with calculations.
Mini summary: Dynamic parameters update based on calculations.
Definition: You can use a parameter to control a table calculation, like changing the number of periods in a moving average.
Why important: It gives users control over the calculation.
Simple explanation: Like a slider that changes the window size for a moving average.
Real-life example: Parameter to choose the number of months for a moving average.
School example: Parameter to choose the number of tests to average.
Home example: Parameter to choose the number of days for a moving average.
Nigerian example: Parameter to choose the number of seasons for a moving average of harvest.
PARAMETER IN TABLE CALCULATION Moving Average with parameter [Window Size]
Mini summary: Parameters can control table calculations.
Definition: You can use IF statements to create categories, then use table calculations on those categories.
Why important: It gives you powerful insights.
Simple explanation: First, you decide what group something belongs to, then you calculate across groups.
Real-life example: IF sales are high, then calculate the running total of high sales.
School example: IF student is in grade A, then rank them.
Home example: IF expense is food, then calculate total food expenses.
Nigerian example: IF crop is maize, then calculate running total of maize harvest.
COMBINED EXAMPLE IF [Sales] > 1000 THEN "High" ELSE "Low" END Then Running Total of Sales for each category.
Mini summary: You can combine IF and table calculations for deeper analysis.
Definition: Best practices are rules to make your calculations clear and correct.
Why important: They prevent errors and make your work easy to understand.
Simple explanation: Like following a recipe to avoid mistakes.
Real-life example: Name your calculations clearly, like "Running Total of Sales".
School example: Use comments in your formulas to explain what they do.
Home example: Test your calculations with small data to make sure they work.
Nigerian example: Always check the direction of your table calculation.
BEST PRACTICES - Use clear names. - Add comments (// comment). - Test with small data. - Check the direction. - Keep it simple.
Mini summary: Follow best practices to create reliable calculations.
Definition: You can build a dashboard that uses IF statements, table calculations, and parameters.
Why important: It shows your skills in action.
Simple explanation: You create a dashboard that a business can use.
Real-life example: A sales dashboard with Running Total, Moving Average, and a parameter for discount.
School example: A grade dashboard with IF for pass/fail, Running Total of scores, and a parameter for pass mark.
Home example: A budget dashboard with IF for spending categories, Running Total of expenses, and a parameter for savings goal.
Nigerian example: A farm dashboard with IF for crop health, Running Total of harvest, and a parameter for price.
DASHBOARD EXAMPLE +--------------------------------------+ | Sales Dashboard | | +----------+ +---------------------+ | | | IF Sales | | Running Total | | | | Category | | of Sales | | | +----------+ +---------------------+ | | +----------+ +---------------------+ | | | Parameter| | Moving Average | | | | Discount | | of Sales | | | +----------+ +---------------------+ | +--------------------------------------+
Mini summary: Combine all tools to build a powerful dashboard.
Condition
|
V
Is it true?
|
+--+--+
| |
Yes No
| |
V V
Do A Do B
Month Sales Running Total Jan 100 100 Feb 120 220 (100+120) Mar 130 350 (220+130) Apr 150 500 (350+150)
Month Sales Moving Avg (3 months) Jan 100 - Feb 120 - Mar 130 116.7 (100+120+130)/3 Apr 150 133.3 (120+130+150)/3
| Feature | IF Statement | Table Calculation |
|---|---|---|
| Purpose | Make decisions | Compute across rows |
| Creates | New categories | New calculations |
| Example | IF Sales > 1000 THEN "High" | Running Total of Sales |
| Type | What it shows | Best for |
|---|---|---|
| Running Total | Cumulative sum | Seeing growth |
| Moving Average | Smoothed trend | Seeing general direction |
Fantastic work! You have learned three powerful tools: IF statements, table calculations, and dynamic parameters.
IF statements help you make decisions in your data. Table calculations show patterns across rows β like running totals and moving averages. Dynamic parameters change automatically to make your dashboards smarter.
By combining these tools, you can create advanced analyses that help people make better decisions.
You are now ready to tackle even more complex data challenges!
Match the term with its description.
| Term | Description |
|---|---|
| 1. IF Statement | A. Adds up as you go |
| 2. Running Total | B. Makes decisions |
| 3. Parameter | C. User-changeable value |
| 4. Moving Average | D. Smoothes data |
Answers: 1-B, 2-A, 3-C, 4-D
Scenario: You are a data analyst for a school. You have student scores and want to create a dashboard.
In groups of 4, collect data on daily temperatures for 2 weeks. Create a dashboard with: IF statement for hot/cold, Running Total of temperatures, Moving Average (3-day), and a parameter to change the moving average window. Present your dashboard.
Create a dashboard of your study hours. Include: IF statement for productive/unproductive, Running Total of hours, Moving Average of hours, and a parameter to change the goal. Share with a friend.
Project: Create a sales dashboard for a small shop. Include:
Present your dashboard.
Using Tableau Public, create a dashboard with:
Publish and share the link.
Create a story with 4 pages: Page 1 β IF statement classification, Page 2 β Running Total, Page 3 β Moving Average with parameter, Page 4 β Combined insights. Use your own data. Share the story link.
(Answers provided within the multiple choice and matching sections above.)
In the next module, we will explore advanced visualisations like Gantt charts, waterfall charts, and scatter plots. We will also learn how to use sets and groups for deeper analysis.
Make sure you are comfortable with IF statements, table calculations, and parameters.
Get ready to create even more stunning and insightful visualisations!
End of Module 8 Β· Keep making smart calculations!