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Microsoft Power BI Cookbook

You're reading from   Microsoft Power BI Cookbook Convert raw data into business insights with updated techniques, use cases, and best practices

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781835464274
Length 598 pages
Edition 3rd Edition
Languages
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Authors (2):
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Greg Deckler Greg Deckler
Author Profile Icon Greg Deckler
Greg Deckler
Brett Powell Brett Powell
Author Profile Icon Brett Powell
Brett Powell
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Toc

Table of Contents (16) Chapters Close

Preface 1. Installing and Licensing Power BI Tools 2. Accessing, Retrieving, and Transforming Data FREE CHAPTER 3. Building a Power BI Semantic Model 4. Authoring Power BI Reports 5. Working in the Power BI Service 6. Getting Serious About Date Intelligence 7. Parameterizing Power BI Solutions 8. Implementing Dynamic User-Based Visibility in Power BI 9. Applying Advanced Analytics and Custom Visuals 10. Enhancing and Optimizing Existing Power BI Solutions 11. Deploying and Distributing Power BI Content 12. Integrating Power BI with Other Applications 13. Working with Premium and Microsoft Fabric 14. Other Books You May Enjoy
15. Index

Forecasting with What-If Analysis

Power BI can be used to directly support the creation of forecasts, budgets, and other planned values of future business measures and events. The relationships and logic of these semantic models, which are commonly implemented in Excel formulas and maintained by business teams, can be efficiently replicated within a dedicated Power BI Desktop file. Isolating the what-if input variables from the forecast creation, storage, and visualization in Power BI enables users to more easily create, analyze, and collaborate on business forecasts.

In this recipe, a Power Desktop model is used to ingest forecast-variable inputs from Excel and process these variables with a dynamic transformation process to generate a forecast table available for visualization. This design enables business teams to rapidly iterate on forecasts, and ultimately supports an official or approved forecast or plan that could be integrated with other semantic models.

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