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Hands-On SQL Server 2019 Analysis Services

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

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Product type Paperback
Published in Oct 2020
Publisher Packt
ISBN-13 9781800204768
Length 474 pages
Edition 1st Edition
Languages
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Author (1):
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Steven Hughes Steven Hughes
Author Profile Icon Steven Hughes
Steven Hughes
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Table of Contents (19) Chapters Close

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

Prepping data for tabular models

With multidimensional models, a star schema is required in the underlying data source. However, with tabular models, a star schema is not required. This means that data preparation is not as clear as it is with multidimensional models. In this section, we will explore some key considerations that are involved when preparing data for tabular models.

Contrasting self-service and managed deployments

Tabular model designs have their origins in self-service technologies such as Power BI and Excel. Why does this matter? Because well-designed dimensional models still perform better and are easier to develop solutions for. Self-service models often focus only on the immediate business need and not on lasting performance or growth. When the number of consumers of an analytics model is one or just a few, the impact is minimal. However, when scaling the models beyond a limited set of users, performance and usability become key considerations in design.

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