Data Science Integration

This content is part of the Tableau Blueprint Methodology. Meet Tableau Blueprint(Link opens in a new window).

Data science teams use a rapidly evolving and heterogeneous set of tools to draw insights from data. When teams can tie these tools directly into interactive visualizations in Tableau, cutting edge analysis can be seen and understood across organizations. As of Tableau 2020.1, the Analytics Extensions API creates a new frontier for extending Tableau by allowing developers to integrate new programming languages and software with Tableau’s dynamic calculation language, bringing all stakeholders in the data science process together.

Along with the release of the API, Tableau’s existing Python, R, and MATLAB External Services are known as “Analytics Extensions.” The Analytics Extensions API is based off of the original TabPy External Services API, and TabPy can be considered Tableau’s reference API implementation. Users can connect to their own services through the TabPy/External API connection type in Tableau with support for passing credentials via basic authentication and SSL.

One of the core scenarios for Analytics Extensions is the integration of predictive models into Tableau visualizations. Dynamic integrations allow for real-time predictions on the latest data, flexible scenario testing, and predictions on filtered datasets that would be too large to pre-compute. Combining advanced statistical analytics with Tableau gives you the ability to enable users of all skill levels to reap the benefits without deep knowledge of the underlying statistical packages and functions. Additional configuration in Tableau Server is needed to enable external advanced analytics functionality.

For more details about the Analytics Extensions API, join the Tableau Developer Program.

Thanks for your feedback!