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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

Installing and Configuring Power BI Desktop

Power BI Desktop is the primary tool used to develop the visual and analytical content that is then deployed and collaborated on in the Power BI service, embedded in other applications and portals, or even shared on the public internet. Although Power BI Desktop runs as a single application, it includes three tightly integrated components with their own options and settings:

  • The Power Query and Power Query Editor experience, with its underlying M language and data mashup engine.
  • The Analysis Services tabular data modeling engine and its DAX analytical language.
  • The interactive reporting and visualization engine.

Configuring and leveraging these capabilities, in addition to advanced analytics and customization features such as R, Python, mobile layout, and natural language queries, makes it possible to build robust and elegant BI and analytics solutions.

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