ARTICLES ...

Introduction to MSSQL Server Analysis Services


Creating Our First Cube
Working with Dimensions
Handling Time Dimensions
Parent-Child Dimensions
Working with the Cube Editor
Exploring Virtual Cubes
Custom Cubes: Financial Reporting
Custom Cubes: Financial Reporting - Part II
Drilling Through to Details: From Two Perspectives
Reporting Options for Analysis Services Cubes:            MS Excel
Reporting Options for Analysis Services Cubes: MS FrontPage
Reporting Options for Analysis Services Cubes: Cognos PowerPlay
Build a Web Site Traffic Analysis Cube: Part I
Build a Web Site Traffic Analysis Cube: Part II
MSAS Administration and Optimization: Simple Cube Usage Analysis
MSAS Administration and Optimization: Toward More Sophisticated Analysis
Using Calculated Cells in Analysis Services, Part I
Using Calculated Cells in Analysis Services, Part II
Reporting Options: ProClarity Professional, Part I
Reporting Options: ProClarity Professional, Part II
Putting Actions to Work in Regular Cubes
Actions in Virtual Cubes
Introduction to Local Cubes
Another Approach to Local Cube Design and Creation
Creating a Dynamic Default Member
Derived Measures vs. Calculated Measures
Basic Storage Design
Partitioning a Cube in Analysis Services - An Introduction
Performing Incremental Cube Updates - An Introduction
Semi-Additive Measures and Periodic Balances
Distinct Count Basics: Two Perspectives
Manage Distinct Count with a Virtual Cube
Point-and-Click Cube Schema Simplification

MDX, optimization, Performance, optimization, Island Technologies Inc., Bill Pearson, William E. Pearson, III,

Dimension, Query, Cognos, Business Objects, Reporting Services, Conversion, Design, Cube, model

Point-and-Click Cube Schema Simplification

In this article, we will explore another tool that MSAS offers for the enhancement of cube processing, the Optimize Schema option. Optimize Schema attempts to identify unnecessary joins between our fact and dimension tables, and then to remove them. In many cases, the tool works effectively to accomplish this, leading to a significant reduction in a cube’s processing time.  Elimination of the joins means more rapid resolution of MSAS’ queries to the relational database, upon which our cube is dependent as a data source.  This, in turn, means that data is pulled into Analysis Services in less time, contributing to a more rapid cube build overall.

The operation of the Optimize Schema option takes advantage of a common circumstance within the construction of many star or snowflake schemas:  the foreign key that serves as the basis of a join between the fact table and a given dimension table is identical to the member key itself. When this is the case, MSAS can eliminate the join, and source the member key directly from the fact table, instead of relying upon a join to the dimension table to obtain the key.

In this article, we will examine the use of Optimize Schema in making our cubes process faster. To accomplish this objective, we will:

  • Overview the Optimize Schema option;
  • Create a copy of the Warehouse sample cube for use in our practice session;
  • Prepare the cube copy further by processing;
  • Discuss the Member Key Column property, and examine existing settings within our practice cube;
  • Discuss possible considerations in determining the appropriateness of the use of the Optimize Schema option in our respective business environments;
  • Perform a practice exercise within which we employ the Optimize Schema option;
  • Examine some of the effects of using Optimize Schema.

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SYNOPSIS & CONCEPTS :
 Synopsis:

Simplify an Analysis Services cube schema with point-and-click simplicity, eliminating joins between dimension and fact tables. MSAS Architect Bill Pearson  leads a hands-on introduction to using this option to significantly reduce cube processing time.

Concepts:

  • Analysis Services

  • OLAP

  • Cube

  • MSSQL Server

  • MDX

  • Optimize

  • Derived

  • Schema

  • Performance

  • Member

  • Key

  • Column

  • Join

  • Editor

  • Dimension

  • Property

  • Query

  • Processing

  • Calculated Member

  • Property
     

   
 

 

About the Series:

This article is a member of the series Introduction to MSSQL Server 2000 Analysis Services. The series is designed to provide hands-on application of the fundamentals of MS SQL Server 2000 Analysis Services, with each installment progressively adding features and techniques designed to meet specific real - world needs. For more information on the series, as well as the hardware / software requirements to prepare for the exercises we will undertake, please see my initial article, Creating Our First Cube.
Optimize, Schema, Performance, Member, Key, Column, Join, Cube, Editor, Dimension, Analysis, Services, MSAS, Property, Query, Processing, MDX, Cube, design, Calculated, Member, Property, Query, processing, Performance, Editor, MDX, MSSQL, Server, Analysis, Services, optimization

All Contents Copyright Island Technologies Inc. ®  Island Technologies® and Island Technologies Inc.®  are registered trademarks of Island Technologies Inc., protected in the United States and other countries.  For information, contact Island.

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