Power BI is a business intelligence and analytics services tool by Microsoft designed to provide visual and interactive insights into data. This book will provide thorough, technical examples of using all primary Power BI tools and features as well as demonstrate high impact end-to-end solutions that leverage and integrate these technologies and services.
Build effective analytical data models, reports, and dashboards using the advanced features of Power BI.
Purchase of the print or Kindle book includes a free eBook in the PDF format.
Key FeaturesThe 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.
What you will learnIf you're a BI professional who wants to up their knowledge of Power BI and offer more value to their organization, then this book is for you. Those looking for quick solutions to common Power BI problems will also find this book an extremely useful resource. Please be aware that this is not a beginner's guide; you'll need a solid understanding of Power BI and experience working with datasets before you dive in.