Book Image

Introducing Microsoft SQL Server 2019

By : Kellyn Gorman, Allan Hirt, Dave Noderer, Mitchell Pearson, James Rowland-Jones, Dustin Ryan, Arun Sirpal, Buck Woody
Book Image

Introducing Microsoft SQL Server 2019

By: Kellyn Gorman, Allan Hirt, Dave Noderer, Mitchell Pearson, James Rowland-Jones, Dustin Ryan, Arun Sirpal, Buck Woody

Overview of this book

Microsoft SQL Server comes equipped with industry-leading features and the best online transaction processing capabilities. If you are looking to work with data processing and management, getting up to speed with Microsoft Server 2019 is key. Introducing SQL Server 2019 takes you through the latest features in SQL Server 2019 and their importance. You will learn to unlock faster querying speeds and understand how to leverage the new and improved security features to build robust data management solutions. Further chapters will assist you with integrating, managing, and analyzing all data, including relational, NoSQL, and unstructured big data using SQL Server 2019. Dedicated sections in the book will also demonstrate how you can use SQL Server 2019 to leverage data processing platforms, such as Apache Hadoop and Spark, and containerization technologies like Docker and Kubernetes to control your data and efficiently monitor it. By the end of this book, you'll be well versed with all the features of Microsoft SQL Server 2019 and understand how to use them confidently to build robust data management solutions.
Table of Contents (15 chapters)

Introduction to tabular models

SQL Server Analysis Services tabular models are very different compared to multidimensional models because, with tabular semantic models, data can be stored in a highly compressed, in-memory, columnar database designed to support business analytics over small to large volumes of data, in addition to supporting DirectQuery against supported data sources. Tabular models also use tabular modeling structures to store and analyze data:

Figure 10.1: Tabular models use tabular modeling structures, including tables and relationships, to store and analyze data
Figure 12.1: Tabular models use tabular modeling structures, including tables and relationships, to store and analyze data

A common development workflow for developing and deploying a tabular model is to use SQL Server Data Tools (SSDT) for Visual Studio or Visual Studio with Analysis Services extensions to design the model, deploy the model as a database to SQL Server Analysis Services or Azure Analysis Services (AAS), schedule the automatic reprocessing of the data model, and assign user membership...