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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Adding dimensions, attributes, and hierarchies

In SSAS, dimensions are comprised of a group of attributes and hierarchies that define the dimension. Before we get into how, we need to discuss three key topics; that is, dimensions, attributes, and hierarchies:

Dimensions are the slicers we use in our cubes to filter and segment our data for analysis. We defined our dimensions in Chapter 3, Preparing Your Data for Multidimensional Models.
Attributes are the various related items in our dimension. For example, if we use the City dimension, the attributes include City Name, City Key, Country, State or Province, and Last Recorded Population. These are the fields we added to our DSV.
Hierarchies help us organize our attributes. A hierarchy gives us a clear drill path into our data. In our City dimension, we will create a Geography hierarchy that consists of Country, State or Province, and City in that order. The goal of hierarchies is to be able move through our data in...