Book Image

Microsoft Power BI Cookbook - Second Edition

By : Greg Deckler, Brett Powell
Book Image

Microsoft Power BI Cookbook - Second Edition

By: Greg Deckler, Brett 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)
14
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15
Index

Enhancing and Optimizing Existing Power BI Solutions

Power BI projects often begin by focusing on specific functional requirements, such as a set of dashboards and reports for a given business area and team. With relatively narrow requirements and small datasets, sufficient performance and reliability is often achievable without design and code enhancements to the data retrieval, model, and reporting layers. Additionally, Power BI Premium capacity and in certain cases Analysis Services resources provide viable options to enhance the scalability of a dataset.

For larger Power BI projects—particularly when the options of Power BI Premium and Analysis Services are not available—it becomes important to identify opportunities to improve report query performance and to more efficiently use system resources to store and refresh the dataset.

Additionally, the data import process can often be made more resilient and less resource intensive. Furthermore, the application...