Tableau Server Automation

Tableau Server is a powerful business intelligence tool that allows organizations to share, collaborate on, and publish data insights and dashboards. One way to make the most of Tableau Server is through automation, which can help streamline processes and improve efficiency.

Here are some ways to automate Tableau Server:

1. USE TABLEAU SERVER REST API

The Tableau Server REST API allows you to programmatically access and manage Tableau Server resources, such as workbooks, data sources, and users. This can be useful for automating tasks such as publishing workbooks, creating users, and updating data sources.

2. USE TABLEAU SERVER CLIENT (TSC)

TSC is a Python library that allows you to access and manage Tableau Server resources using Python scripts. TSC is particularly useful for automating tasks that require more complex logic, such as refreshing multiple data sources or scheduling extract refreshes.

3. USE TABLEAU SERVER MANAGEMENT ADD-ON (TSMA)

TSMA is a paid add-on for Tableau Server that provides additional tools for managing and automating Tableau Server tasks. With TSMA, you can automate tasks such as creating sites, managing user permissions, and scheduling extract refreshes.

4. USE TABLEAU SERVER'S BUILT-IN SCHEDULING AND ALERTING FEATURES

Tableau Server includes built-in scheduling and alerting features that allow you to automate tasks such as refreshing data sources and publishing workbooks. You can schedule these tasks to run at specific times or when specific conditions are met. By using these automation tools, you can streamline your Tableau Server workflow and save time and resources. Automation can also help ensure that your data is up to date and accurate, as tasks such as data source refreshes can be automated to run on a regular basis

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Comments (5)

  • Dem Jefor Reply

    Great post on building successful data products! I particularly appreciated the emphasis on defining a clear problem or need, as well as the importance of developing a solid data strategy. It's easy to get caught up in the excitement of creating a new product, but these foundational elements are critical for long-term success. I also appreciated the discussion on fostering a culture of data literacy – this is something that I believe is often overlooked, but can make a big difference in terms of the effectiveness and adoption of a data product. Thanks for sharing your insights and experience on this topic!

    January 12, 2021 at 1:38 pm
    • Taul Alisud Reply

      It's great to hear that you found the emphasis on defining a clear problem or need and developing a solid data strategy to be helpful and valuable. You're right that it's important to focus on these foundational elements in order to ensure long-term success.
      I also agree with you that fostering a culture of data literacy is crucial for the effectiveness and adoption of a data product. It's essential for team members to have the skills and knowledge necessary to understand and work with data in order to effectively use a data product.

      January 12, 2021 at 1:38 pm
    • Dem Jefor Reply

      I completely agree that having a clear understanding of the problem or need being addressed, as well as a solid data strategy, are essential for long-term success

      January 12, 2021 at 1:38 pm
  • Callum Smith Reply

    Great insights on data products in this blog! Keep up the good work.

    January 12, 2021 at 1:38 pm
  • Max Vylan Reply

    Your thoughts and ideas are valuable and useful for those looking to build and use data products effectively

    January 12, 2021 at 1:38 pm

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