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Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

By : Greg Deckler, Powell
4.7 (23)
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Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

4.7 (23)
By: Greg Deckler, Powell

Overview of this book

Since its first edition the Power BI Cookbook has been a best-selling resource for BI developers and data analysts to produce impactful, quality BI solutions. This new and updated edition retains the rigorous details and concepts readers of prior editions have enjoyed while also demonstrating powerful new capabilities and updated guidance aligned to the current state of the platform. In this book, with step-by-step instructions, you will learn to navigate the complexities of data integration and visualization in Power BI. From creating robust data models to implementing sophisticated reporting techniques, this Power BI book empowers you to make informed decisions based on actionable insights. It also introduces you to new capabilities such as Hybrid tables and scorecards, enhancing your ability to communicate and analyze business performance. It also expands and improvises on the core of the previous edition like parameterizing Power BI solutions, authoring reports, data intelligence, and integrating advanced analytics. This edition not only updates you on the latest features but also prepares you for future innovations with a preview of upcoming AI enhancements in Power BI. Whether you're refining your skills or aspiring to become an expert, this book is an invaluable resource for leveraging Power BI to its fullest potential
Table of Contents (16 chapters)
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14
Other Books You May Enjoy
15
Index

Leveraging Aggregation Tables

DirectQuery mode is a great tool for overcoming the scalability issues of Import mode, or for providing real-time reporting to business users. However, as user interactions with Power BI reports can generate high volumes of queries, DirectQuery Power BI solutions can overwhelm the resource limits of many data sources, which can entail query queuing and poor user experiences. Aggregation tables and dual-mode storage tables were designed to fix the performance issues associated with using DirectQuery against large semantic models in the millions, billions, and trillions of rows.

Aggregation tables provide Power BI with a more performant, less resource intensive alternative to processing queries. As queries from report visuals are received by the semantic model, the model determines whether to use an aggregation table and its related tables or if, given the columns and metrics required, it’s necessary to query the larger, more granular source...

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