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Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

By : Greg Deckler, Powell
4.8 (12)
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Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

4.8 (12)
By: Greg Deckler, Powell

Overview of this book

The complete everyday reference guide to Power BI, written by an internationally recognized Power BI expert duo, is back with a new and updated edition. Packed with revised practical recipes, Microsoft Power BI Cookbook, Second Edition, helps you navigate Power BI tools and advanced features. It also demonstrates the use of end-to-end solutions that integrate those features to get the most out of Power BI. With the help of the recipes in this book, you’ll gain advanced design and development insight, practical tips, and guidance on enhancing existing Power BI projects. The updated recipes will equip you with everything you need to know to implement evergreen frameworks that will stay relevant as Power BI updates. You’ll familiarize yourself with Power BI development tools and services by going deep into the data connectivity, transformation, modeling, visualization, and analytical capabilities of Power BI. By the end of this book, you’ll make the most of Power BI’s functional programming languages of DAX and M and deliver powerful solutions to common business intelligence challenges.
Table of Contents (16 chapters)
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14
Other Book You May Enjoy
15
Index

Embedding Statistical Analyses

Statistical analysis beyond basic aggregations is typically implemented outside of business intelligence semantic models by data scientists and data science applications. When possible, however, it is much more efficient to leverage existing data models, Power BI skills, and the features used for other Power BI reports and dashboards—such as the Analytics pane described earlier in this chapter.

In this recipe, the data points supporting a linear regression model are created from an existing Power BI data model. This model is then analyzed and described via DAX measures, with values such as slope, Y-intercept, and the Z-score for residuals. Finally, a rich report page is constructed to visualize the strength and accuracy of the regression model and to detect outliers.

Getting ready

To prepare for this recipe, follow these steps:

  1. Open a Power BI Desktop file locally and access the Power Query Editor by clicking on Transform...

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