Book Image

Microsoft Tabular Modeling Cookbook

By : te Braak
Book Image

Microsoft Tabular Modeling Cookbook

By: te Braak

Overview of this book

Business Intelligence Semantic Models (BISM) is a technology that is designed to deliver analytical information to users through a variety of mechanisms that include model structure, definition, and design. This book demonstrates how to create BISM models so that information can be presented to users in an intuitive and easy-to-use format. Once the model is defined, we also show you how it can be managed and maintained so that the data in it remains current and secure. Microsoft Tabular Modeling Cookbook is an all-encompassing guide to developing, managing, creating, and using analytical models using the Business Intelligence Semantic Model (BISM). This title covers a range of modeling situations and common data analysis related problems to show you the techniques required to turn data into information using tabular modeling. Microsoft Tabular Modeling Cookbook examines three areas of tabular modeling: model development, model management and maintenance, and reporting. This book is a practical guide on how to develop semantic models and turn business data into information. It covers all phases of the model lifecycle from creation to administration and finally reporting. It also shows you how to create models which are designed to analyze data. All sections of BISM modeling from development to management and finally reporting are covered. The sections on development examine a wide range of techniques and tricks required to build models, including moving data into the model, structuring the model to manipulate the data, and finally the formulas required to answer common business questions; all of these are discussed in this book in detail. Finally, the book examines methods of reporting on the data within the model, including the creation of data-driven workbooks and reports for a powerful end user experience.
Table of Contents (13 chapters)
12
Index

Deriving tables and selecting top n records

As a comparison to DAX, SQL is a mature language that has a variety of mechanisms for temporarily defining and using tables. One of the reasons for using this type of feature is that a result may need to be pre-computed before it is applied in the outer constructs of a query.

Consider the situation of accumulating sales based on the sales values' ranks, as shown in the following screenshot:

Deriving tables and selecting top n records

This type of query must pre-compute values before they can be used. Logically, the query must determine each customer's sales value, then rank the customers based on that value, and then (finally) determine (on a row-by-row basis) the total value of sales for all rows with a lower rank. Clearly, there is an order to implement this type of query because one set of values cannot be calculated before the other is complete. Using temporary structures is an excellent method for achieving this.

Unfortunately, there is no declaration to derive a temporary table...