Hello Reader,

Imagine you’re about to cook a new recipe.

Before you start, you gather and organize all your ingredients. You figure out what you have, what you're missing, and how to use the best ingredients.

EDA, or Exploratory Data Analysis, is like this. It's the crucial prep work in understanding your data, spotting patterns, identifying outliers, and uncovering relationships.

Without EDA, you risk making decisions based on incomplete or misunderstood data, which can lead to costly mistakes.

The good news is that Tableau can make Exploratory Data Analysis (EDA) easy.

But remember, EDA isn’t just about Tableau—it’s a critical skill that can be transferred to any data analysis tool. The principles and steps you learn in EDA with Tableau are applicable to other tools like Python, R, Excel, or Power BI.

How to use Tableau for EDA

Tableau can be a game-changer for EDA. Its intuitive interface and powerful visualization capabilities can help simplify the process.

Here’s how it can help with EDA:

• Ease of Use: Drag-and-drop functionality makes it accessible, even for beginners.
• Visual Clarity: Use different charts and graphs to see data trends and outliers clearly.
• Interactive Dashboards: Instantly explore data with dynamic, interactive dashboards.

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Pro Tips for Effective EDA in Tableau

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1 Ask Broad Questions, then Get More Specific.

Start with broad questions and get more specific as you go.

For example, begin with “How are overall sales?”.
Then “how are sales trending this year?”.
Then drill down to “Which products are driving the most sales in Q2?”

Then start again with another broad question - this time targeting a different set of data points.

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2 Explore, Explore, Explore
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Sometimes just dragging and dropping to see what you find out about the data can help you.
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Don’t be afraid to try different visualizations.

• Create a horizontal or vertical bar chart to compare values.
• Create a line chart to see trends over time.
• Then add another dimension to make a small multiple - see if the patterns or observations change.

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3 Leverage Tooltips​
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Customize tooltips to provide extra context. Tooltips allows you to get additional details without cluttering the main visualizations.

For example, if you have sales data, you can customize tooltips to show profit margins when hovering over a product in your bar chart. This extra layer of information helps you understand which products are not just selling well but also contributing most to your bottom line.

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4 Filter for Focus​
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Use filters to narrow down your data.

This keeps your visualizations focused and avoids overwhelming with too much information.

Seeing different groups in isolation sometimes give different perspectives.

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5 Set Context with Reference Lines ​
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Reference lines can be great in adding context - especially when you're comparing against certain thresholds or goals.

For example, include a line showing the average profit amount, which can help in quickly assessing performance.

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Your Turn to Explore

There are many other strategies to try.

The keyword in EDA roots from the word "explore", which means to search or discover.

So go ahead and try different things out.

Using Tableau for EDA transforms a tedious task into something that's more fun. It’s about exploring, asking questions, and letting the data guide you to answers.

With Tableau, you’re not just looking at data; you’re interacting with it, uncovering observations stories, which eventually can influence decisions and strategies.

And remember, the skills you develop in EDA with Tableau are transferable to other tools, making you a more versatile and capable data analyst.

I'd love to hear how you use Tableau for your EDA. Do you have any special techniques? Or do you use other tools?

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Until next time,

Donabel