I've created a python notebook that helps to automate review and testing of Power BI reports. It embeds a report and then works through every (visible) page and exports the data from every (visible and exportable) visual.

In this newsletter, we’ll dive into hierarchical directories and how they’re used in analytics. Let's clarify what we mean.

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Power BI can connect to, transform and visualise data. Which is great but how do we get that modified data out?

One way is using a Power Automate flow to connect to the published Power BI dataset.

In this video we discuss how to manage a notebook PySpark code throughout the deployment pipeline stages, so that it adjusts dynamically to each deployment stage without needing manual interaction.