You're reading from Hands-On SQL Server 2019 Analysis Services Design and query tabular and multi-dimensional models using Microsoft's SQL Server Analysis Services

Product type Paperback

Published in Oct 2020

Publisher Packt

ISBN-13 9781800204768

Length 474 pages

Edition 1st Edition

Languages

SQL

Tools

SQL Server

Concepts

Data Analysis

Author (1):

Steven Hughes

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Table of Contents (19) Chapters

Preface

1. Section 1: Choosing Your Model

2. Chapter 1: Analysis Services in SQL Server 2019 FREE CHAPTER

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

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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...