Tableau is a requirement for data science
Integration of data science
Data science teams use a set of rapidly evolving, diverse tools to extract insights from data. If teams can incorporate these tools directly into interactive visualizations in Tableau, current analyzes can be presented visually and made understandable for the entire company. Starting with Tableau 2020.1, the scope of application for Tableau is expanded using the Analytics Extensions API. With this API, developers have the option of integrating new programming languages and software into the dynamic calculation language of Tableau and thus integrating everyone involved in the data science process.
Like the existing external services Python, R and MATLAB from Tableau, this newly published API is one of the "Analytics Extensions". The Analytics Extensions API is derived from the original TabPy API for external services. TabPy is a kind of reference API implementation for Tableau. Users can connect to their own services using the TabPy / External API connection type in Tableau. The transfer of credentials via simple authentication and SSL is supported.
One of the core scenarios for analytics extensions is the integration of forecast models in Tableau visualizations. Dynamic integration enables real-time forecasts based on current data, flexible scenario tests and forecasts based on filtered databases that are too large to be calculated in advance. By combining advanced statistical analytics with Tableau, users of all skill levels can take advantage of the features without deeper knowledge of the underlying statistical packages and functions. Additional configuration of Tableau Server is required to enable advanced external analytics functionality.
For detailed information on the Analytics Extensions API, we recommend participating in the Tableau Developer Program.
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