Updated on 20 Oct 2021

Tableau vs Excel – When to Use Tableau and When to Use Excel

Ned Krastev
Published on 12 Jun 2018 6 min read

Tableau vs Excel is a hot discussion topic in the data science community. Indeed, Excel is not a top resume-building skill for aspiring data scientists. But it has been around for ages and you are probably familiar with tons of useful Excel tricks for data cleaning and analysis.

Are you curious to find out more about Tableau, too?

In this article, we will take a deeper look at the Tableau vs Excel dilemma. Both are used for data analysis. But top-notch tools such as Tableau are what distinguishes successful Business Intelligence (BI) analysts from average performers.

Tableau has grown to become one of the most popular business intelligence tools in the world. It is a BI software that allows non-technical users to visualize their data and work with it almost immediately, lowering know-how barriers dramatically.

Author’s note: If you are interested in learning more about the data science field and the career opportunities it offers, go ahead and download our free data science career guide.

The BI Analyst Job: Using Tableau

In the past, business analysts needed the help of IT personnel who would assist them in gathering raw data and pre-processing it.

The BI Analyst job is becoming easier with Tableau

Only then could business analysts start working on the visualization of such data.

The advent of Tableau democratized data visualization

Tableau allowed BI analysts to be independent. Non-technical people can easily load data into the program and start playing with it. Tableau’s forte is meaningful and intuitive visualizations. And sometimes that’s really valuable. Analysts are able to explore their data right away, without spending too much time on numbers which provide limited insights and instead focus on data that matters.

This is why we can confidently say that Tableau is an indispensable tool in the arsenal of most corporate business intelligence analysts, data analysts, and data scientists. (On a sidenote, being familiar with the business basics is crucial for a successful data science career. If that falls within the scope of your interests, check out our article 5 Business Basics for Data Scientists.)

Tableau vs Excel: What Are the Differences?

Many people are uncertain about the difference between Tableau and spreadsheet tools like Excel. And that’s a reasonable doubt until we point out they serve different purposes. Using Tableau doesn’t necessarily mean you can forget about Excel and vice versa.

While Excel is not as powerful or intuitive as Tableau when it comes to data visualization, Tableau is not optimal when you would like to use it as a data creation tool.

When Tableau is not the optimal solution

Although it has several database management functionalities, the program isn’t the best solution when you would like to perform multiple operations with your data before you start analysing it. Moreover, Tableau isn’t great for multi-layered calculations. It is able to calculate its own fields, but it shouldn’t be used as a spreadsheet tool for multi-layered calculations such as the preparation of a budget in Excel.

What Are the Benefits of Tableau?

Where Tableau surpasses the competition is in data visualizations.

Data visualization is Tableau's key strength

It is a very smart program that allows you to visualize data in a more powerful way compared to Excel.  

Tableau is designed to make the most of geodata

So, for example, when you work with geographical data, there is no way Excel could interpret the cells in your spreadsheet as a geographical location. On the other hand, Tableau recognizes that and allows you to visualize such data and see how a variable is distributed geographically.

Make the most of geodata with Tableau

Data Visualization in Tableau: Build a Stunning Dashboard by Combining Several Types of Charts

Moreover, Tableau allows you to combine several types of charts and build up meaningful dashboards that are truly interactive and facilitate additional analysis. Once you visualize your data, you can easily dig deeper and explore its granularity, finding the reason for unusual spikes or investigating certain trends.

Tableau is a time-saver

Even novice Tableau users would be able to save a significant amount of time if they transfer their pre-designed existing Excel dashboards to Tableau. Uploading new data and updating visuals is more rapid in Tableau. (To learn how load data in Tableau, check out our tutorial Connecting Data Sources to Tableau.)

Tableau vs Excel

Integrating Tableau With SQL for Smarter and Faster Insights

If you have an enormous amount of data in SQL, you may want to interpret it, right? Connecting Tableau with SQL can certainly help. Tableau has the power to quickly deliver sophisticated visual analyses, so the tool is a perfect match for SQL.

You Don't Need to Choose Between Tableau and Excel

Therefore, we can agree that a competent analyst needs both Excel and Tableau given that they serve different purposes. Tableau is superior when it comes to visuals and dashboards, and Excel is a spreadsheet tool we need in order to perform multi-layered calculations.

Tableau vs Excel: We need both Tableau and Excel!

In the same way a combat soldier carries a rifle and a pistol at the same time and uses them under different circumstances, a business analyst should know how to work with both Excel and Tableau and apply each of them when needed.

P.S. Want to find out more about Tableau? Check out our Tableau tutorials. Or maybe you fancy working with Excel? Then feel free to jump to these Excel tutorials.

Try Introduction to Tableau course for free!  

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Ned Krastev

Co-founder of 365 Data Science

Ned is a Master of Finance at Bocconi University with years of advisory experience in some of the world’s top international enterprises. A visionary and co-founder of 365 Data Science, he has helped thousands of students gain competitive advantage through his courses Introduction to Excel, Advanced Microsoft Excel, Data Analysis with Excel Pivot Tables, Python for Finance, and Introduction to Tableau.

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