Chapter 15. Using External Connections in Tableau

There are many use cases where you would want to rely on the external connections to R or Python in Tableau. The most obvious one, from the content in this book, is to rely on R and Python to run advanced statistical models and incorporate them into a dashboard or data visualization. However, if you allow your imagination to guide you for a moment, you’ll discover additional potential use cases. Here is a list of other things you could do using external connections that I haven’t covered in this book:

Advanced chart types

Wrangling the data to develop advanced visualizations can be a challenge that R and Python can support. This opens a lot of new chart types that are harder to develop in Tableau without support.

Custom calculations and data manipulation

Ideally, you would prep your data before loading it into Tableau. However, these external connections can be used to shape your data in different ways and return new values.

Advanced user experience

By combining parameters and external connections, you could create new and exciting ways to receive input from your user in Tableau and return values back to them or write the input to a database.

Integration with external APIs and web services

R and Python have extensive library ecosystems, including modules for working with external APIs and web services. Tableau users can leverage scripts to connect to external data sources, pull in real-time data, and incorporate that ...

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