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.
Table of Contents (19 chapters)
1
Section 1: Choosing Your Model
4
Section 2: Building and Deploying a Multidimensional Model
8
Section 3: Building and Deploying Tabular Models
12
Section 4: Exposing Insights while Visualizing Data from Your Models
15
Section 5: Security, Administration, and Managing Your Models

Chapter 6: Preparing Your Data for Tabular Models

Tabular models are the newer analytics model structure implemented in SQL Server. The underlying analysis engine is columnar, not multidimensional, which means there are some different considerations for data preparation. The VertiPaq analysis engine was originally introduced in Excel and now supports Power BI datasets and Analysis Services tabular models. The technology behind VertiPaq uses a number of column-based algorithms to improve storage and performance. This technology allows Analysis Services to compress and structure the data for optimized performance. One other key design change is that tabular models match various relational data structures and are not reliant on a dimensional model for success.

In this chapter, we will look at the range of options, from minor preparation to star schema-based approaches. We will walk through prototyping tabular models with Excel Power Pivot capabilities. Because tabular models can be...