Tableau and the open source advantage

Tableau is an innovator in the field of data visualization with its ease of use, stunning visualizations, vibrant community, and more contributing to success. Tableau recognizes that the way we use data today and the field of analytics is much different now than even a decade ago. There are currently strong offerings in both closed and open source software, and with Tableau, you get the best of both options as developers. 

Visualization is, and I expect will always be, important to understand and help democratize data. However, improved hardware and machine learning algorithms are demonstrating that data users need tools that both show them things while also enhancing and supporting their learning.

Why does open source matter? 

Open source software dominates the machine learning (ML) and artificial intelligence (AI) landscape. Tensorflow and PyTorch help to greatly simplify the practice of training and deploying machine learning algorithms. R and Python have also grown in usage at universities, where analytics courses teach the next batch of analysts and data users how to solve problems that even five years ago were unthinkable by most. 

Not only are these tools open source, but they are liberally licensed for commercial use. Licenses like Apache, MIT, and BSD 3-clause cover a large swath of these tools and place very little restriction on how they are used. 

Why does open source matter for Tableau?

Tableau recognizes the importance of these open source tools in the data space. The tools themselves are impressive, and more importantly, they come with a large network of experts and enthusiasts that know how to leverage them. 

Rather than trying to develop similar tools, Tableau has opened up critical parts of its ecosystem to them. And this enables the large community of open source contributors to extend Tableau while allowing Tableau customers to best integrate the tools and technologies they choose to use.

Why does it matter for customers?

The field of business intelligence is complex; companies have varying data sources, business processes, and reporting needs. A one-size-fits-all solution to reporting simply doesn’t exist and won’t do the trick in our complex business environment. Tableau is an amazing tool that can help solve a lot of your reporting needs, but expecting it to do everything, I think is unrealistic.

Open source software can help fill in the gaps that your company will inevitably find in its data and analytics journey. Fortunately, there is enough content to cover all experience levels!

Do you have a programmer handy that knows how to build machine learning models? Great! They can continue to build those great models and easily convert them into visualizations using a tool like TabPy. Not yet ready for machine learning algorithms? You’d be surprised at how effective your analysts and interns can be with a tool like pandas, and fortunately, you can use pantab to push that data into Tableau. 

Useful open source libraries for Tableau

To get started and experience more when building on the Tableau Developer Platform, I wanted to share a collection of helpful resources—some that were already mentioned, but bears repeating— and other tools you may find useful. I expect more options will pop up in the future.

• TabPy allows you to execute Python scripts in Tableau workbooks
• pantab provides easy serialization of pandas DataFrames to Hyper extracts
• Tableau Server Client is a Python wrapper for the Tableau Server REST API
• hyperarrow is a new, language-agnostic serializer/deserializer of Arrow tables to and from Hyper extracts

How to learn more

To engage the open source community, there are several ways to get involved, regardless of skill level. As a beginner, simply ask questions on the Tableau Forums or StackOverflow is a great place to start. Open source maintainers want their tools to be used, so you will often find a direct line of contact to them through Forums.

As a developer, contributing code to these tools is an effective way to engage the community. You can help make the tools better, enhance your coding skills and knowledge, and most importantly, build an amazing portfolio to advance your career.

A single blog post won’t do justice to the entire ecosystem of open source tools that surround Tableau. To learn more, join the Tableau Developer Program and engage the open source community directly.