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Hands-On SQL Server 2019 Analysis Services

You're reading from  Hands-On SQL Server 2019 Analysis Services

Product type Book
Published in Oct 2020
Publisher Packt
ISBN-13 9781800204768
Pages 474 pages
Edition 1st Edition
Languages
Author (1):
Steve Hughes Steve Hughes
Profile icon Steve Hughes
Toc

Table of Contents (19) Chapters close

Preface 1. Section 1: Choosing Your Model
2. Chapter 1: Analysis Services in SQL Server 2019 3. Chapter 2: Choosing the SQL Server 2019 Analytic Model for Your BI Needs 4. Section 2: Building and Deploying a Multidimensional Model
5. Chapter 3: Preparing Your Data for Multidimensional Models 6. Chapter 4: Building a Multidimensional Cube in SSAS 2019 7. Chapter 5: Adding Measures and Calculations with MDX 8. Section 3: Building and Deploying Tabular Models
9. Chapter 6: Preparing Your Data for Tabular Models 10. Chapter 7: Building a Tabular Model in SSAS 2019 11. Chapter 8: Adding Measures and Calculations with DAX 12. Section 4: Exposing Insights while Visualizing Data from Your Models
13. Chapter 9: Exploring and Visualizing Your Data with Excel 14. Chapter 10: Creating Interactive Reports and Enhancing Your Models in Power BI 15. Section 5: Security, Administration, and Managing Your Models
16. Chapter 11: Securing Your SSAS Models 17. Chapter 12: Common Administration and Maintenance Tasks 18. Other Books You May Enjoy

Using database views and data source views

So far, the focus has been on prepping the star schema in the relational database so that you can build out the multidimensional model. This section will focus on a design decision that impacts database design, but also impacts how you work with Analysis Services itself. As part of building out a multidimensional model, data source views are created in Analysis Services to serve as the mapping between the relational and multidimensional models:

Figure 3.4 – Data source view in SQL Server 2019 Analysis Services from Visual Studio

We will now look at the pros and cons of data source views.

Data source views – pros and cons

Data source views (DSVs) are an integral part of a multidimensional model project. This is where the source data is modeled for the multidimensional model. In the preceding screenshot, the star schema can be clearly seen. The preceding model has been pulled directly from the underlying...

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