Book Image

Hands-On SQL Server 2019 Analysis Services

By : Steve Hughes
Book Image

Hands-On SQL Server 2019 Analysis Services

By: Steve Hughes

Overview of this book

SQL Server Analysis Services (SSAS) continues to be a leading enterprise-scale toolset, enabling customers to deliver data and analytics across large datasets with great performance. This book will help you understand MS SQL Server 2019’s new features and improvements, especially when it comes to SSAS. First, you’ll cover a quick overview of SQL Server 2019, learn how to choose the right analytical model to use, and understand their key differences. You’ll then explore how to create a multi-dimensional model with SSAS and expand on that model with MDX. Next, you’ll create and deploy a tabular model using Microsoft Visual Studio and Management Studio. You'll learn when and how to use both tabular and multi-dimensional model types, how to deploy and configure your servers to support them, and design principles that are relevant to each model. The book comes packed with tips and tricks to build measures, optimize your design, and interact with models using Excel and Power BI. All this will help you visualize data to gain useful insights and make better decisions. Finally, you’ll discover practices and tools for securing and maintaining your models once they are deployed. By the end of this MS SQL Server book, you’ll be able to choose the right model and build and deploy it to support the analytical needs of your business.

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Table of Contents (19 chapters)
Preface
Preface
Who this book is for?
What this book covers?
To get the most out of this book
Download the example code files
Download the color images
Conventions used
Get in touch
Reviews
1
Section 1: Choosing Your Model
Section 1: Choosing Your Model
Free Chapter
2
Chapter 1: Analysis Services in SQL Server 2019
Chapter 1: Analysis Services in SQL Server 2019
What is SQL Server Analysis Services anyway?
Why use SQL Server Analysis Services?
What's new in SQL Server Analysis Services 2019?
What are the tools used with SQL Server Analysis Services?
One last thing – our sample data
Summary
3
Chapter 2: Choosing the SQL Server 2019 Analytic Model for Your BI Needs
Chapter 2: Choosing the SQL Server 2019 Analytic Model for Your BI Needs
Technical requirements
Understanding how we got here – two modes
Discovering multidimensional model strengths and challenges
Discovering tabular model strengths and challenges
Understanding other differences that matter
Choosing the model type for business-specific reasons
Summary
Further reading
4
Section 2: Building and Deploying a Multidimensional Model
Section 2: Building and Deploying a Multidimensional Model
5
Chapter 3: Preparing Your Data for Multidimensional Models
Chapter 3: Preparing Your Data for Multidimensional Models
Technical requirements
A short primer on dimensional modeling
Designing and building dimensions and facts
Loading data into your star schema
Using database views and data source views
Prepping our database for the multidimensional model
Summary
6
Chapter 4: Building a Multidimensional Cube in SSAS 2019
Chapter 4: Building a Multidimensional Cube in SSAS 2019
Technical requirements
Creating the Analysis Services project in Visual Studio
Adding dimensions, attributes, and hierarchies
Adding cubes and measure groups
Summary
7
Chapter 5: Adding Measures and Calculations with MDX
Chapter 5: Adding Measures and Calculations with MDX
Technical requirements
Introducing MDX basics – SELECT, FROM, WHERE
Adding calculations and measures to your cube
Adding KPIs to our cube
Exploring more MDX expressions
Summary
8
Section 3: Building and Deploying Tabular Models
Section 3: Building and Deploying Tabular Models
9
Chapter 6: Preparing Your Data for Tabular Models
Chapter 6: Preparing Your Data for Tabular Models
Technical requirements
Prepping data for tabular models
Data optimization considerations
Prototyping your model in Excel with Power Pivot
Summary
10
Chapter 7: Building a Tabular Model in SSAS 2019
Chapter 7: Building a Tabular Model in SSAS 2019
Technical requirements
Creating the solution and first tabular model
Creating a tabular model with DirectQuery
Creating a tabular model on transactional data
Importing a Power Pivot model into Analysis Services
Deploying and processing your completed models
Summary
11
Chapter 8: Adding Measures and Calculations with DAX
Chapter 8: Adding Measures and Calculations with DAX
Technical requirements
Understanding the basics of DAX
Adding columns and measures to the tabular model
Creating measures with the CALCULATE function
Working with time intelligence and DAX
Creating calculated tables
Creating calculation groups
Creating KPIs
Querying your model with SQL Server Management Studio and DAX
Summary
12
Section 4: Exposing Insights while Visualizing Data from Your Models
Section 4: Exposing Insights while Visualizing Data from Your Models
13
Chapter 9: Exploring and Visualizing Your Data with Excel
Chapter 9: Exploring and Visualizing Your Data with Excel
Technical requirements
Connecting Excel to your models
Building visualizations with your models
Building and enhancing an Excel dashboard
Advanced design with CUBE functions
Sharing your Excel dashboards with others
Summary
14
Chapter 10: Creating Interactive Reports and Enhancing Your Models in Power BI
Chapter 10: Creating Interactive Reports and Enhancing Your Models in Power BI
Technical requirements
Creating Power BI visualizations using live connections
Understanding live connections and import for Power BI with SSAS models
Adding measures to Power BI when using tabular models and live connections
Deploying your Power BI report to a Power BI workspace
Summary
15
Section 5: Security, Administration, and Managing Your Models
Section 5: Security, Administration, and Managing Your Models
16
Chapter 11: Securing Your SSAS Models
Chapter 11: Securing Your SSAS Models
Technical requirements
Reviewing security settings for SSAS
Setting up user roles in servers and databases
Implementing data security in multidimensional models
Implementing data security in tabular models
Summary
17
Chapter 12: Common Administration and Maintenance Tasks
Chapter 12: Common Administration and Maintenance Tasks
Technical requirements
Understanding the languages
Backing up and restoring SSAS databases
Processing or refreshing the data in your models
Scaling your models
Discovering how your models are performing
Reviewing other maintenance tasks or tools
Summary
18
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Data optimization considerations

Another consideration when preparing your data for tabular models is the data refresh options available. Typically, data is imported into your tabular model similar to the process we used with multidimensional models. Imported data is loaded into memory and optimized by the VertiPaq engine. This involves a high level of compression, including columnar data storage techniques. The functions of compression and memory combine to create an optimized model with performance. Here are some key considerations when using data refresh:

  • Refresh frequency: The data is only as fresh as the last import. If the data source has been updated recently, the data may be out of sync. This is less of an issue when you are loading data from a data warehouse. The data warehouse is typically loaded in batches as well. If you match your refreshes to the batch loads, your data will be consistent with the data warehouse. If you have chosen to use the transactional database...
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