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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
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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
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Manuel Quintana
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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

Dataset design process


With the data warehouse bus matrix as a guide, the business intelligence team can work with representatives from the relevant business teams and project sponsors to complete the following four-step dataset design process:

  1. Select the business process.
  2. Declare the grain.
  3. Identify the dimensions.
  4. Define the facts.

Selecting the business process

Ultimately each business process will be represented by a fact table with a star schema of many-to-one relationships to dimensions. In a discovery or requirements gathering process it can be difficult to focus on a single business process in isolation as users regularly analyze multiple business processes simultaneously or need to. Nonetheless, it's essential that the dataset being designed reflects low level business activities (for example, receiving an online sales order) rather than a consolidation or integration of distinct business processes such as a table with both online and reseller sales data:

  • Confirm that the answer provided...
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