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

Concepts

Data Analysis

Author (1):

Steve Hughes

Table of Contents (19) Chapters

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

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Understanding live connections and import for Power BI with SSAS models

The reports we created in the previous section connect live to the multidimensional and tabular models in Analysis Services. When using this capability, queries are sent to Analysis Services and the results are returned. While some caching is done to improve performance, the overall solution is dependent on the performance of Analysis Services and the network connectivity with Power BI.

The alternative approach is to import the data, which results in the data being loaded into memory in Power BI. This is most valuable when you need to mash up data between multiple data sources. However, if you are working with SSAS to import a lot of data, you will find there are often performance issues when importing that much data. You will likely be required to create MDX or DAX queries to make sure the data can be mashed up as expected. Refreshing performance with multidimensional models has proven to be a poor solution...