Is Tableau a Programming Language? (Explained!)

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You’ve just recently heard about Tableau as a great skill to learn. You might be slightly unsure or even confused as to whether Tableau is considered a programming language. Not to worry, here’s the short answer to this question: Is Tableau a Programming Language?

Tableau is not a programming language. Tableau is largely different from programming languages: Tableau is a data visualization software but programming languages provide instructions to a computer for output. However, Tableau does use a language, VizQL (Visual Query Language), to translate SQL code into visuals.

Now that you have a clearer understanding that Tableau is not a programming or coding language, you might also be curious to know more about the underlying proprietary language VizQL used by Tableau. Tableau and programming languages actually do share some common functions, which might have been the cause for your confusion. If you’re interested in knowing more about Tableau and its relations to programming languages, do read on!

What Can Be a Considered as a Programming Language?

Any language that can execute instructions for computer programs can be considered as a programming language. A programming language is written code that executes a set of instructions that is understandable by computers through binary code. Programming languages typically have syntax (formatting) and semantics (meaning).

How is Tableau Different from a Programming Language?

Tableau is actually really different from a programming language and you’ve probably thought so because of some small confusion. But not to worry, let me share with you the main differences between Tableau and programming languages.

The main difference between Tableau and programming languages is that Tableau is simply a data visualization software but programming languages are written code that allows the execution of a computer program. Both of them are completely different types of technology altogether.

Here are some differences between the functions of Tableau and programming languages:

DifferencesTableauProgramming Languages
Data TransformationLimitedExtensive, done through various packages and libraries
CalculationsAvailable through calculated fields using formula languageAvailable across almost all programming languages through the use of operators, can be further enhanced by packages too
Data VisualizationSimple but powerful drag and drop data visualizationLimited and non-intuitive data visualization through packages

What is Tableau?

Tableau is a business intelligence software made by Tableau Software for the use of creating dashboards and data visualizations. It is a skill commonly used by data analysts, data scientists, and business intelligence analysts. It uses an underlying language called VizQL to process queries but does not require any programming from the user’s end.


VizQL is Tableau’s visual query language for databases. It’s the language that connects the queries and processes them to produce data visualizations. However, you won’t be able to write in this language as it only runs on the background processes. So don’t worry too much about VizQL, just be rest assured that Tableau requires no coding of VizQL from your part.

If you’re looking for more information about VizQL and how it is being used in Tableau, do check out their blog here.

How is Tableau Similar to a Programming Language?

Despite the main difference between Tableau and programming languages, some languages commonly used in data analytics actually do have similar functions to that of Tableau.

Here are the 3 ways Tableau is similar to programming languages.

  1. Data Visualization Functions
  2. Data Transformation Functions
  3. Data Storage

1. Data Visualization Functions

Some programming languages have libraries or packages that provide extra functions to their base language. For example, you’ll want to be using packages such as ggplot2, Plotly, and Matplotlib. These packages allow you to build data visualizations similar to those in Tableau like bar charts, line graphs, and scatterplots.

2. Data Transformation Functions

Tableau’s data transformation functions include merging tables and building relations among them to prepare for data. This can also be commonly found among programming languages through packages like Pandas and dplyr.

3. Data Storage

Just like in Tableau’s data storage capabilities using Tableau Data Extracts programming languages also do allow temporary storage of data. For example, in both Python and R, data can be stored in the form of dataframes in memory when coding.

What Are Some Examples of Programming Languages in Data Analytics?

Programming LanguagePopular Packages in Data Analytics
1PythonPandas, Plotly, Matplotlib, Dash
2Structured Query Language (SQL)
3Rdplyr, ggplot2

1. Python

Let’s start with the most commonly used language you’ve probably already heard of – Python. The Python programming language is one that’s commonly used in data analytics for its powerful scripting capabilities and add-on libraries for data transformation and data visualization. Here are some common libraries in Python that are similar to Tableau:

Link: Python Website

2. Structured Query Language (SQL)

Another popular programming language used by data analysts is Structured Query Language (SQL). SQL is a query language for databases that can be similar to Tableau when you consider how both of them can merge tables! If you’re curious to know more about SQL, you can read more about it in my other post about SQL as a programming language here.

Link: Wiki on SQL

3. R

Commonly used among statisticians and data scientists, the R programming language draws many similarities when you compare it with Tableau. R programming has one of the best (in my own opinion) data visualization packages out there – ggplot2. Here are some of the packages commonly used in R programming:

Link: R Website

4. Javascript

Here’s one last language that’s used the least by data analysts but also provides some great data visualizations – Javascript! The D3.js package is one that I’ve been hearing most about because of its large variations in visuals.

Links: Javascript, D3

Where Should You Learn Tableau?

Beginner-friendly: For those among you who are new to Tableau, I would recommend heading over to the Tableau Learning resources available here for a great resource that’s perfect for complete beginners. They provide a comprehensive introduction to Tableau Desktop that can be useful for beginners.

Visual Learners: If you’d like to learn via video format, you can check out my other blog post on Tableau Webinars that can give a great overview of the basics of Tableau!

Structured Learning: Alternatively, if you prefer a structured way of learning, you can start with this course on Coursera for a good introduction to Data Visualization with Tableau. This course is perfect for serious learners that won’t mind paying a little more for curated and structured information all in one place! Do check it out!

Is Programming Needed for Tableau?

Programming is not required for Tableau for basic use. Tableau offers drag-and-drop functionalities for building charts and dashboards without the need for coding. However, Tableau users can use Python and R code to enhance visualizations and build models.

Here’s an article I wrote about programming in Tableau with more details about whether Tableau and coding, do check it out if you’re curious to know more!

What Language Does Tableau Use?

Tableau uses the VizQL language. VizQL (Visual Query Language) is a proprietary language from Tableau Software that works beneath the queries and interactions made to produce data visualizations. However, VizQL only runs on the backend and does not require user input to create data visualizations in Tableau.

Final Thoughts

I hope that by the time that you’re reading this, you’ll be very confident in your knowledge that Tableau is not a programming language. In fact, I hope that you’ve cleared up any confusion between the 2 through this blog post. I hope it’s been useful for you too! Thanks for reading!

My Favorite Data Learning Resources:

Here are some of the learning resources I’ve personally found to be useful as a data analyst and I hope you find them useful too. These may contain affiliate links and I earn a commission from them if you use them. However, I’d honestly recommend them to my juniors, friends, or even my family!

Recommended Online Course Provider: I find Coursera online courses the most well-structured and comprehensive! You can get a Coursera Plus Membership to get started here.

Using my link, you’ll only pay $1 for your first month (Offer ends 4 December 2021). I’d recommend using this to just get started, with just a small cost, and if you find that it’s not for you, you can always cancel before the next month!

Learning Data Analytics: I really like the Google Data Analytics Professional Certificate program made by Google, because of its credibility and focus on the skills required as a data analyst. You’d get the first month off of the subscription using my link!

Learning Tableau: Tableau is my main data visualization tool for work. I recommend going for Data Visualization with Tableau for an online course and Practical Tableau by Ryan Sleeper.

Learning Python: I’d recommend Learning Python for Data Analysis and Visualization for an online course and Python for Data Analysis as a resource book.

Learning Power BI: Power BI is a great tool I use for my personal projects and analysis for its lower cost. Getting Started with Power BI Desktop is a great online course to start with and Beginning Microsoft Power BI is a good book to accompany your learning.

Learning R: The Data Science: Foundations using R Specialization online course is real solid one you should check out. For books, I’d recommend Learning R.

Learning SQL: A good started course is Introduction to SQL from Datacamp and for books, SQL: The Ultimate Beginners Guide: Learn SQL Today should be a useful resource while you learn.

Learning Data Visualization: I personally think that the Big Book of Dashboards is an excellent book for reference when designing your dashboards, especially on Tableau.

To see all of my most up-to-date recommendations, check out this resource I’ve put together for you here.


A budding data analyst with great interest in writing all things about data!

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