Book Image

Tabular Modeling with SQL Server 2016 Analysis Services Cookbook

By : Derek Wilson
Book Image

Tabular Modeling with SQL Server 2016 Analysis Services Cookbook

By: Derek Wilson

Overview of this book

SQL Server Analysis Service (SSAS) has been widely used across multiple businesses to build smart online analytical reporting solutions. It includes two different types of modeling for analysis services: Tabular and Multi Dimensional. This book covers Tabular modeling, which uses tables and relationships with a fast in-memory engine to provide state of the art compression algorithms and query performance. The book begins by quickly taking you through the concepts required to model tabular data and set up the necessary tools and services. As you learn to create tabular models using tools such as Excel and Power View, you’ll be shown various strategies to deploy your model on the server and choose a query mode (In-memory or DirectQuery) that best suits your reporting needs. You’ll also learn how to implement key and newly introduced DAX functions to create calculated columns and measures for your model data. Last but not least, you’ll be shown techniques that will help you administer and secure your BI implementation along with some widely used tips and tricks to optimize your reporting solution. By the end of this book, you’ll have gained hands-on experience with the powerful new features that have been added to Tabular models in SSAS 2016 and you’ll be able to improve user satisfaction with faster reports and analytical queries.
Table of Contents (18 chapters)
Tabular Modeling with SQL Server 2016 Analysis Services Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Introduction


When developing a tabular model, you have two primary choices for where and how the data is stored and accessed from end user tools. Tabular models are unlike SQL Server Analysis Services Multidimensional models, which only store all data to disk. Tabular models by default store data in memory with an option for storing data to disk when appropriate. By storing the data in memory there is faster query performance since there is no disk I/O for retrieving data results. Modeling can be accomplished in visual studio and does not require a full data transformation or load process which speeds up the time to develop and deploy the model to production. This chapter focuses on the available storage modes for tabular models, in-memory mode and DirectQuery mode. You will learn how each mode operates and best practices for choosing the appropriate mode for your solution.

Understanding query modes

There are two unique values that you can choose to implement the query mode in your model....