9. Tableau Foundations

🎯 Learning Goals

Identify the purpose of Tableau and its role in data visualization

Understand basic features of Tableau, including dimensions and measures

Create simple visualizations using Tableau

📗 Technical Vocabulary

Tableau

Data Visualization

Dashboard

Dimensions

Measures

Dataset

📊 What is Tableau?

Tableau is a leading data visualization tool that allows users to create interactive and shareable dashboards. With Tableau, you can transform raw data into clear, understandable visual stories through charts, maps, and graphs.

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For example, imagine a city using Tableau to visualize its monthly water consumption. Instead of just seeing numbers in a report, the city can create graphs that highlight trends — maybe they notice that water use spikes every summer! This makes it easier to communicate insights and guide decision-making.

At KWK, we will explore how to use Tableau to tell compelling stories with data!

Dimensions and Measures

The building blocks of working with Tableau are the concepts of dimensions and measures.

Dimensions: Categories that describe data, such as names, dates, or locations. Think of dimensions as the labels that help you group your data.

Some people may refer to these dimensions as ‘blue pills’

Measures: Numerical values that can be measured or aggregated. This could be sales figures, temperatures, or any number that you can sum or average.

Some people may refer to these dimensions as ‘green pills’

✏️

Try-It | Dimension or Measure? Below are six examples. For each, decide whether it is a dimension or a measure.

Score

Measure

Customer Name

Dimension

Total Revenue

Measure

Product Price

Measure

Order ID

Dimension

Date of Birth

Dimension

✨ Getting Started with Tableau

Let’s start by creating a data visualization together to build your understanding! For our first example, we’re going to create a bar chart showing the top movies by rating. ➡️

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OUR DATA: To use Tableau, you first need to connect to a data source like an .csv, SQL database, Excel file or Google Sheets. Once connected, Tableau pulls the data so you can start working with it.

For today’s lesson, we’ll be working with IMDB Movies Dataset. Please note: this is the Kaggle version, which we’ve linked out so you have the context. Please make sure you’re working with the KWK version, since it has already been cleaned:

KWK_IMDB_dataset_cleaned.csv

115.5KB

✨

CREATING YOUR FIRST DATA VISUALIZATION

0. Make a Tableau account

Head to
public.tableau.com

Click Sign In in the upper right hand corner

Select Create an account

1. Create a Viz

Head to
public.tableau.com

Click your profile in the upper right hand corner

Click Create a Viz to get started

2. Connect Your Data

Download the dataset:

KWK_IMDB_dataset_cleaned.csv

115.5KB

Select Upload from computer and upload the.

You may need to click Create Extract in the upper-right hand corner.

🥳

As you can see, Tableau automatically divides our data into dimensions and measures (you’ll have to click on a worksheet to see this).

3. Explore Tableau

Let’s explore the Tableau interface! There are a few key panels that help you create and interact with data visualizations.

🔢

Data pane - displays dimensions (categorial fields) and measures (numerical fields) and allows users to drag & drop fields into the workspace

📄

Sheets, Dashboards, and Story tabs - users can switch between individual sheets (visualizations), dashboards (collections of sheets), and stories (narrative sequences of dashboards/sheets)

🚣‍♀️

Rows & Columns shelves - used to place dimensions and measures to structure the visualization and determines how data is plotted

🟨

Marks card - allows for customizing the appearance and visual elements of charts like color, size, label, detail, tooltip, and shape

📖

Filters and pages shelf - allows filtering of data based on specific dimensions or measures; breaking data into multiple pages

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View / worksheet area - central canvas where visualizations are displayed

There are three essential building blocks in Tableau. Each plays a different role in how you explore, create, and present data:

We’ll mostly be working in various worksheets today. You can create new worksheets, workbooks, or dashboards by click on the bottom of the screen.

There’s also one super cool tool, we saved the best for last, the Show Me feature! ✨ Show Me is a smart recommendation tool that suggests the best types of visualizations based on the data fields you select. It provides a range of chart options, highlighting those that are most appropriate given the dimensions and measures in use.

4. Explore Your Data

Before diving into building a visualization, take 1-3 minutes to familiarize yourself with the dataset. A good data scientist always conducts an initial exploration to understand the structure, key variables, and potential insights before building visualizations. Think about what questions you can ask from the data. If something seems unclear, you can always revisit the Kaggle dataset description for more details.

✏️

Try-It | Explore Your Data

Click on the Data Source tab in Tableau to examine the structure of your dataset

Review field types and understand how your data is organized. What does each row represent?

Answer one of the following reflection/discussion questions

What data points interest you in this dataset and why?
What potential challenges do you see in this dataset?

5. Build Your Data Visualization

Let’s say we want to make a data visualization that shows movies by movie rating in descending order, drag Name into Rows and Rating to Columns. Change the rating measure from Sum to Average:

Tada! You have your first Tableau data visualization! Since you changed the data visualization, make sure you change the sheet name at the bottom

6. Save Your Work

Before we move on to other cool things you can do with Tableau, let’s talk about saving your work and how to get back to it. In the toolbar, go to File → Publish As and type in a descriptive name for your dashboard.

To reopen your work, go to your profile, click on the data visualization you want to work on, and click the edit icon.

7. Sharing Your Work

Congratulations ! You’re now ready to share your work, maybe with your IL, your friends, anyone! You can do this by going to your profile, clicking on the Viz you’d like to share, and selecting the share button.

✏️

Let’s create more data visualizations together! For each of the following goals, be sure to create a new worksheet in Tableau and rename it before getting started.

🥅 Goal #1: Create a bar chart that displays the Number of Ratings per Movie

Create a new worksheet by clicking the "New Worksheet" icon at the bottom of the screen.

Rename your worksheet by right-clicking on the tab and selecting "Rename," then type "Ratings Count by Movie". You can also double-click.

Set up your visualization:

Find the name field in the Dimensions section (blue pills) of the Data pane.

Drag name to the Rows shelf.

Find the num_raters field in the Measures section (green pills) of the Data pane.

Drag num_raters to the Columns shelf.

Tableau will automatically create a horizontal bar chart. We could switch the rows and columns, but the way it is currently set up works better for movie names since they can be long.

Sort your visualization:

Click on the sort button in the toolbar (it looks like ↑↓ with bar graphs).

Select "Sort Descending" to arrange movies from highest to lowest number of ratings.

This will show the most-rated movies at the top of your chart.

🥅 Goal #2: Create a scatter plot that displays the Rating vs. Number of Raters

Create a new worksheet and rename it "Rating vs Number of Raters”.

Set up your visualization:

Find the num_raters field in the Measures section.

Drag num_raters to the Columns shelf.

Find the rating field in the Measures section.

Drag rating to the Rows shelf.

Find the name field in the Dimensions section.

Drag name to the Detail mark on the Marks card.

What does this step do?

When you drag the name field (which represents the movie title) to the Detail mark on the Marks card, you’re telling Tableau: “Show a separate data point for each movie in the dataset.” Without this, Tableau might try to summarize or group the data. By adding name to Detail, you're making sure that each dot in the scatter plot represents one individual movie, not just an average or a grouped value. This is what allows the scatter plot to display all the movies separately.

Adjust the mark type:

In the Marks card, click the dropdown that currently says "Automatic".

Select "Circle" to create a proper scatter plot.

(Optional) Change the “Size” to 10%

Add a trend line:

What is a trend line?

A trend line is a visual representation of the overall direction or pattern in your data over time. It helps identify whether values are increasing, decreasing, or remaining stable by showing the general trajectory of data points. In Tableau, there are four trend lines you can add. You can read more about them here! For now, we think a linear line should suffice.

Click on the Analytics tab (next to the Data tab on the left side).

Find "Trend Line" in the list of analytics objects.

Drag "Trend Line" onto the view where it says "Add a trend line".

In the dialog that appears, select "Linear" and click "OK".

The trend line will show if there's a correlation between number of raters and rating

To undo a trend line, you can drag it out of your data visualization.

🥅 Goal #3: Create a line chart that shows the Movie Ratings over the Years

Create a new worksheet and rename it "Ratings Trends by Year".

Set up your visualization:

Find the year field in the Dimensions section.

Drag year to the Columns shelf.

Find the rating field in the Measures section.

Drag rating to the Rows shelf.

Adjust the aggregation:

By default, Tableau will use SUM(rating), which isn't meaningful.

Click on the dropdown arrow on SUM(rating) in the Rows shelf.

Select "Measure (Sum)" > "Average" to show the average rating for each year.

If it doesn’t happen automatically, create the line chart:

In the Marks card, click the dropdown that currently says "Automatic".

Select "Line" to create a line chart.

This will show how average movie ratings have changed over time.

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Think About It: Tableau Foundations

Creating effective data visualizations is only the first step in data analysis. The true value comes from interpreting these visualizations, understanding their significance, and communicating insights effectively. Looking back at the data visualizations you just created, answer the following questions:

What are the top 2-3 headlines you would share about these visualizations?

How might movie studios or streaming platforms use this information to inform their decisions?

What limitations does this visualization have, and what additional data might enhance its value?

📝

Practice: Build Your Own Data Visualization

Now that we’ve built a few visualizations together, it’s your turn to explore! Create two additional data visualizations in this IMDB dataset that we haven’t yet.

A little blocked? Here are some questions if you need help getting started…

Do movies with more reviews tend to have higher or lower ratings?

What is the trend of the number of movies released per year?

Do longer movies (in run time) tend to get better ratings?

Which year had the most highly-rated movies?

🌶️🌶️ Medium challenge: use filtering to find interesting patterns!

🌶️🌶️🌶️ Spicy challenge: try using calculated fields to dig deeper into the dataset!

For a summary of this lesson, check out the 9. Tableau Foundations One-Pager!