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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
Author Profile Icon Mitchell Pearson
Mitchell Pearson
Brian Knight Brian Knight
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Brian Knight
Devin Knight Devin Knight
Author Profile Icon Devin Knight
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 2. Data Transformation Strategies FREE CHAPTER 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

Dataset planning


After the source data has been profiled and evaluated against the requirements identified in the four-step dataset design process, the BI team can further analyze the implementation options for the dataset. In almost all Power BI projects, even with significant investments in enterprise data warehouse architecture and ETL tools and processes, some level of additional logic, integration, or transformation is needed to enhance the quality and value of the source data or to effectively support a business requirement. A priority of the dataset, planning stage is to determine how the identified data transformation issues will be addressed to support the dataset. Additionally, based on all available information and requirements, the project team must determine whether to develop an import mode dataset or a DirectQuery dataset.

Data transformations

To help clarify the dataset planning process, a diagram such as the following can be created that identifies the different layers of...

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