Is Programming Needed for Tableau? (Answered!)


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If you’re coming from a non-data background, one of the first questions you might ask is – if programming is needed for you to use Tableau effectively. Regardless of your background, I thought it would be good to set things out clearly. Here’s a quick answer.

Programming is not needed for Tableau for basic use. Tableau offers drag-and-drop functionalities for building charts without the need for coding and is not designed for data cleaning through programming. However, advanced Tableau users can use Python and R code to enhance visualizations and build models.

Now that you know you would be having much less trouble having to learn to program when using Tableau, you might be thinking of not learning to program at all. Let me share with you why having some additional knowledge of programming can help enhance your analysis.

Let’s get right to the content!

Why Is There No Programming Required in Tableau?

1. Tableau is built for Data Visualization

If you’ve tried your hand on Tableau, you’ll quickly understand that it is built for the larger audience, to produce quick insight for businesses through beautiful data visualizations. I can personally say that with firsthand experience, Tableau has a large focus on building out charts and dashboards.

Such focus on generating visuals tends to allow less flexibility on how the data is handled. In most programming languages for data work like Python and R, the codes are generally used for cleaning data and applied statistics. Therefore the Tableau software would not require programming from the users.

2. No Programs Need to be Written

Building upon the point mentioned above, the focus of Tableau is on data visualization. As most of the work done for plotting charts is automated through a high-level drag-and-drop experience, beginner-level users can easily pick up this skill with basic statistics training.

This drag-and-drop approach drops the need for Tableau to give the user extra headache having to manually input code just for simple plotting of charts.

Therefore, to cut down on too many extra features and customizability, there is no requirement for coding just to use Tableau at the base level.

3. Data is Typically Cleaned Beforehand

If you are at a stage of considering Tableau for your business intelligence plan or for personal skills development, you should understand that there are steps to be taken before reading data into Tableau.

As much as Tableau offers custom SQL joins, it has limitations on how the data can be handled after reading into the software.

Therefore, whatever data enters Tableau has to be and is typically cleaned through various ETL methods beforehand.

That’s why I would conclude that it would not be necessary to have programming experience for Tableau use.

How Can Some Programming Knowledge Help in Tableau?

1. Analytical Thinking

If you’ve been exposed to some level of coding, you would have understood how to think in an analytical sense. You’d definitely have a greater advantage in learning Tableau with the help of these concepts.

For example, through building charts in Tableau, you would need to insert multiple dimensions into a single chart to produce useful insight.

In such cases, the analytical thought processes of someone with a background in programming in either Python or R would allow such a higher level of analysis.

2. Similar Data Visualizations and Understanding of Data

Tableau offers visualizations that are largely similar to most statistical charting available in Matplotlib in Python or ggplot2 in R. Essentially the overall processes are the same in building charts. These similarities allow for a quicker grasp of plotting graphs in Tableau by a programmer.

Programming in Python and R to produce visualizations out of raw data is no easy feat.

Anyone with experience in these programming languages would understand the importance of data quality and would be able to pick out good data points better.

3. Easier Understanding of Formulae

In Tableau, there are fields that can be input with certain formulae to be used to make custom charts or basic descriptive statistical tests. These are called calculated fields. They offer more flexibility in your calculations and they are very much similar to the base functions found within programming languages.

For example, some of these basic functions can include, SUM, COUNT, and COUNTD.

SUM()
COUNT()
COUNTD()

These are common functions used when programming in Python or R for data science and analytics. I would say that having some transferrable knowledge of such functions might be of some help in your analysis in Tableau, although not by much.

4. Python and R Code Integrations

Within the calculated fields of Tableau, there are options to run code from within Tableau to be used in advanced analysis. This is done by adding a code block or your preferred programming language into these fields. Next, these fields can then be drag-and-dropped into your rows and columns to build better visualizations.

For example, great execution of this can be through the use of the caret package on R to help build a machine learning clustering model. The code used to build that model is added into a calculated field and added to an existing scatterplot built in Tableau.

Tableau is able to take that code and apply the machine learning model to show clustering on your visualization through colored clusters. How amazing is that!

Here’s a video demonstration I found of this integration in action:

The only caveat about this application is that there’s no actual need for programming to do a basic analysis or when you’re just starting out in Tableau.

Additional Questions

Is Tableau Hard to Learn?

Tableau is not hard to learn. Tableau is a simple data visualization tool that is not hard for beginners to pick up easily. However, to have in-depth analysis, advanced techniques in Tableau are needed. Therefore, Tableau can be hard if a learner is planning to master Tableau.

Should You Learn Programming Just for Tableau?

No, you should not pick up programming just for Tableau. Since the use of Python or R is only used in very advanced and specific cases in calculated fields, you are unlikely to encounter such a need that soon.

However, I believe that you should already be considering picking up a language that can clean and wrangle data to complement your skills in Tableau. This should be useful for you if you are looking into taking on more data work.

Should You Learn Programming or Tableau First?

Programming should be learned first before Tableau. Learning programming provides the basic foundations of piecing together highly customizable data visualizations that will help in long-term development. However, Tableau can be learned first if the learner prefers a beginner-friendly interface and better practical use.

Based on my personal experience, I believe that you should learn to program first if you have not done so. It would provide you with better options for data visualizations and increased flexibility in creating charts. Some may argue that Tableau should be learned first because of its beginner-friendly interface.

While this may be true, I think that only individuals who are accustomed to business or BI should be learning Tableau first.

Can You Learn Tableau Without Programming?

Tableau can be learned without programming. Tableau is a simple data visualization tool that does not require any programming knowledge. Learning Tableau is possible for anyone new to data visualization. However, having some knowledge of programming languages helps the understanding of calculated fields in Tableau.

Where Can You Start Learning Tableau?

For pure beginners of Tableau, I would recommend heading over to the Tableau Learning resources available here. They provide a comprehensive introduction to Tableau Desktop for beginners.

Alternatively, you can start with this course on Coursera for a good introduction to Data Visualization with Tableau.

Final Thoughts

Tableau may be a new concept to many but rest assured that programming is not needed for basic use. Therefore, unless you are looking to take your data visualizations to the next level, you would not be required to use programming for Tableau.

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.

Austin

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

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