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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

Scaling your models

There are two ways to scale in the database world – scale up or scale out – and they apply to Analysis Services models. Both options bring more compute, memory, and storage to support better performance or larger models.

Scaling up is a pure hardware play. This involves adding more resources to your environment such as RAM or CPUs. In this scenario, bigger is better. For example, you can choose to increase compute capacity by adding CPUs to a server, vCPUs to a virtual machine, and swapping in newer CPUs with more cores. In these situations, you typically leave the SSAS instance in place and it will consume the expanded resources. Scaling up has limits, as you would suspect. You can only scale so far.

The next option is to scale out. Relational databases in many cases do not natively support scale-out scenarios. However, SSAS scales out very well. Both tabular and multidimensional models are designed to scale out to support processing, model...

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