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Microsoft Power BI Complete Reference

You're reading from   Microsoft Power BI Complete Reference Bring your data to life with the powerful features of Microsoft Power BI

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Product type Course
Published in Dec 2018
Publisher Packt
ISBN-13 9781789950045
Length 794 pages
Edition 1st Edition
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Authors (5):
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Brett Powell Brett Powell
Author Profile Icon Brett Powell
Brett Powell
Mitchell Pearson Mitchell Pearson
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Mitchell Pearson
Brian Knight Brian Knight
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Brian Knight
Devin Knight Devin Knight
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Devin Knight
Manuel Quintana Manuel Quintana
Author Profile Icon Manuel Quintana
Manuel Quintana
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Toc

Table of Contents (25) Chapters Close

Title Page
About Packt
Contributors
Preface
1. Getting Started with Importing Data Options FREE CHAPTER 2. Data Transformation Strategies 3. Building the Data Model 4. Leveraging DAX 5. Visualizing Data 6. Using a Cloud Deployment with the Power BI Service 7. Planning Power BI Projects 8. Connecting to Sources and Transforming Data with M 9. Designing Import and DirectQuery Data Models 10. Developing DAX Measures and Security Roles 11. Creating and Formatting Power BI Reports 12. Applying Custom Visuals, Animation, and Analytics 13. Designing Power BI Dashboards and Architectures 14. Managing Application Workspaces and Content 15. Managing the On-Premises Data Gateway 16. Deploying the Power BI Report Server 17. Creating Power BI Apps and Content Distribution 18. Administering Power BI for an Organization 19. Scaling with Premium and Analysis Services 1. Other Books You May Enjoy Index

Summary


In this chapter, we've covered all the components of the data retrieval process used to support the dataset for this project as described in Chapter 7, Planning Power BI Projects. This includes the layer of SQL views within a database source, source connectivity parameters in Power BI Desktop, and the M queries used to define and load the dimension and fact tables of the dataset. In constructing a data access layer and retrieval process for a dataset, we've also discussed the design considerations relative to import and DirectQuery datasets, Power BI Desktop configuration options, and data source privacy levels. Additionally, we've reviewed the core concepts of the M language, including query folding, item access, and data types. Moreover, we've reviewed three examples of efficiently implementing impactful data transformation logic via M queries as well as the tools for developing and editing M queries.

In the next chapter, we'll leverage the M queries and design techniques described...

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