Module 1: OLAP Review

BETA MATERIALS FOR MICROSOFT CERTIFIED TRAINER PREPARATION PURPOSES ONLY Module Strategy How you deliver this course is affected by the nature of the module—that is, the materials revie

BETA MATERIALS FOR MICROSOFT CERTIFIED TRAINER PREPARATION PURPOSES ONLY

to represent any real individual, company, product, or event, unless otherwise noted Complying with all applicable copyright laws is the responsibility of the user No part of this document may

be reproduced or transmitted in any form or by any means, electronic or mechanical, for any purpose, without the express written permission of Microsoft Corporation If, however, your only means of access is electronic, permission to print one copy is hereby granted

Microsoft may have patents, patent applications, trademarks, copyrights, or other intellectual property rights covering subject matter in this document Except as expressly provided in any written license agreement from Microsoft, the furnishing of this document does not give you any license to these patents, trademarks, copyrights, or other intellectual property

 2000 Microsoft Corporation All rights reserved

Microsoft, BackOffice, MS-DOS, Windows, Windows NT, <plus other appropriate product

names or titles Replace this example list with list of trademarks provided by copy editor Microsoft is listed first, followed by all other Microsoft trademarks in alphabetical order > are either registered trademarks or trademarks of Microsoft Corporation in the U.S.A and/or other countries

Content developed by OLAP Train, Inc for Microsoft Corporation and distributed under license The names of companies, products, people, characters, and/or data mentioned herein are fictitious and are in no way intended to represent any real individual, company, product, or event, unless otherwise noted

Other product and company names mentioned herein may be the trademarks of their respective owners

Instructor Notes

A prerequisite for this course is that students have taken course 2074A,

Designing and Implementing OLAP Solutions with Microsoft ® SQL Server ™

2000, or have equivalent experience

This module is a quick review of essential online analytical processing (OLAP) concepts and terminology that students should already be familiar with if they meet the prerequisite For students who have not met the prerequisite, the information in this module is essential for completing the balance of course

2093 Implementing Business Solutions with MDX in Microsoft SQL Server

2000

After completing this module, students will be able to:

! Understand the basic elements of OLAP databases

! Understand the basic definitions and structures of an OLAP cube

! Understand how data flows through an organization’s analytical processes

Materials and Preparation

This section provides you with the required materials and preparation tasks that are needed to teach this module

Required Materials

To teach this module, you need the following materials:

! Microsoft PowerPoint® file 2093A_01.ppt

Preparation Tasks

To prepare for this module, you should:

! Read all of the materials for this module

! Read the instructor notes and margin notes

! Practice the lecture and demonstration

! Complete the labs

! Review the Trainer Preparation materials on the Trainer Preparation compact disc

Presentation:

60 Minutes

BETA MATERIALS FOR MICROSOFT CERTIFIED TRAINER PREPARATION PURPOSES ONLY

Instructor Setup for Group Activities and Labs

This section provides setup instructions that are required to prepare the instructor computer or classroom configuration for group activities and labs All group activities and labs use the same database setup, which requires restoring a database archive

! To prepare for group activities and labs

In this procedure, you restore the Market database, which is a cab file type

1 Start Analysis Manager

2 In the left pane, expand the Microsoft Analysis Services folder

3 Expand the Server icon and verify that the Market database does not exist

4 Right-click the Server icon, and then click Restore Database

5 Navigate to the C:\Moc\2093A\Batches folder

6 Select Market.cab, click Open, and then click Restore

If the Market database already exists from a previous group exercise or lab,

and cubes in the database contain extraneous information, you can return the

Market database and its cubes to a beginning position by either:

Deleting any calculated members that were created in a specific cube, and then saving the cube

- or - Repeating the preceding restore database procedure

Other Activities

Difficult Questions

The following are several difficult questions that students may ask you during the delivery of this module and answers to the questions These materials delve into subjects that are in the scope of the module but may not be specifically addressed in the content of the student notes

1 Can you use dimensions in a purely relational database?

Yes A relational warehouse can make full use of dimensions Adding an OLAP layer defines the relationship between levels of hierarchies in dimensions and can also improve query performance

2 Do you have to purchase SQL Server in order to use Analysis Services?

Yes Analysis Services is bundled with SQL Server However, you can install Analysis Services without using—or installing—SQL Server

3 Is it possible to have a dimension without a hierarchy?

All dimensions have at least one hierarchy A hierarchy may consist of a single level—as is the case in the Measures dimension In that case, you may think of the dimension as not having a hierarchy A dimension can have more than one hierarchy, but in most cases, multiple hierarchies within a dimension are simply treated as separate dimensions with similar names

4 Is Measures a dimension?

When administering a cube, Measures are treated differently from dimensions When using MDX, Measures is simply a dimension with only one level—and no All level

5 Is a cell that is empty—that is, it has no value—still a cell?

Yes The intersection of a member from each dimension forms a cell, whether that cell is populated or not The cell does not take any physical storage space, but a cube is a logical construct and does not reflect the physical storage

BETA MATERIALS FOR MICROSOFT CERTIFIED TRAINER PREPARATION PURPOSES ONLY

Module Strategy

How you deliver this course is affected by the nature of the module—that is, the materials review basic definitions of OLAP databases and structures that

students should already know from the prerequisite course 2074A, Designing

and Implementing OLAP Solutions with Microsoft SQL Server 2000, or from

previous experience

The materials are best presented, therefore, in a didactic format—that is, by questioning students about the definitions and terminologies, then clarifying if the responses are incorrect or vague

Use the following strategy to present this module:

! OLAP Databases Review the basic elements of online analytical processing (OLAP) databases, including how they are different from online transaction processing (OLTP) databases and why they are used for reporting and analysis

Continue with a description of typical end-user applications and how OLAP functionality is incorporated into Microsoft SQL Server 2000 Use examples from your own experience Ask students for examples of applications that might be OLAP candidates from their experience

! OLAP Definitions Materials in this section are an especially important foundation for working with multidimensional expressions (MDX) syntax Review fundamental OLAP definitions, including organization of dimensions, family relationships, and the organization of a cube

! Warehouse Data Flow Present a view of how data flows through an organization’s analytical processes in some companies Focus on the role that MDX plays in the data

flow Then introduce the Sales and other cubes the students will use for

most of this course through the group activity demonstration

Overview

! OLAP Databases

! OLAP Definitions

! Warehouse Data Flow

A prerequisite for this course is that you have taken course 2074A, Designing

and Implementing OLAP Solutions with Microsoft ® SQL Server ™ 2000, or have

the equivalent experience

This module is a quick review of essential online analytical processing (OLAP) concepts and terminology that you should already be familiar with if you meet the prerequisite If you have not met the prerequisite, the information in this

module is essential for completing the balance of course 2093A, Implementing

Business Logic with MDX in Microsoft SQL Server 2000

After completing this module, you will be able to:

! Understand the basic elements of OLAP databases

! Understand the basic definitions and structures of an OLAP cube

! Understand how data flows through an organization’s analytical processes

This is a review module

You need to understand the

basic concepts and

definitions in this module to

successfully complete the

balance of the course

BETA MATERIALS FOR MICROSOFT CERTIFIED TRAINER PREPARATION PURPOSES ONLY

# OLAP Databases

! OLTP vs OLAP Databases

! OLAP for Reporting and Analysis

! OLAP Applications

! OLAP in SQL Server

In this section, you will learn the basic elements of online analytical processing (OLAP) databases, including how they are different from online transaction processing (OLTP) databases and why they are used for reporting and analysis This section continues with a description of typical end-user applications and how OLAP functionality is incorporated into Microsoft SQL Server 2000

Topic Objective

To introduce this section

Lead-in

In this section, you will learn

the basic elements of online

analytical processing

(OLAP) databases

OLTP vs OLAP Databases

$ Specific processing cycle

OLTP databases are characterized by their capabilities for processing online

transactions By contrast, OLAP databases are characterized by their

capabilities for processing online analysis requests from users

OLTP Databases

OLTP databases are used in business applications that support day-to-day business operations OLTP systems are generally characterized by business activity that:

! Is transaction based

You withdraw cash from your account at an automated teller machine (ATM) In the bank’s OLTP database, your withdrawal is a transaction at the lowest level of detail in the bank’s accounting system

! Occurs in real time

When you enter the withdrawal request, cash is dispensed, and your account balance is immediately adjusted This is a real-time transaction that is captured in the OLTP database when it occurs

! Is being continuously processed

The transaction in your account is recorded when the withdrawal occurs Your account and the accounts of others making deposits and withdrawals are being continuously processed

Topic Objective

To compare OLTP and

OLAP databases

Lead-in

OLTP and OLAP databases

have many basic

differences

Ask students to give

examples of OLTP and

OLAP databases from their

own businesses

BETA MATERIALS FOR MICROSOFT CERTIFIED TRAINER PREPARATION PURPOSES ONLY

OLAP Databases

By contrast, OLAP databases are used in applications for analyzing and reporting on business operations OLAP systems are generally characterized by data or business activity that:

! Is summarized

The bank’s internal reporting systems stored in OLAP databases nearly always contain information that is some level of summarization of individual transactions—for example, the total of customer deposits and withdrawals—as opposed to individual transactions

! Is historical

Data is captured and processed for specific time periods, rather than in real time For example, the bank’s reporting of total deposits and withdrawals is only meaningful if summarized by hour, day, week, or month

! Has a specific processing cycle

Data is processed on a specific cycle, rather than continuously The bank’s OLAP database, for example, might be loaded and calculated on a daily or weekly schedule Refreshing the database continuously might create ambiguity about the meaning of the data

OLAP for Reporting and Analysis

! Intuitive Model

$ Drill down and drill up

$ Slice and dice

! Fast and Flexible

Whereas OLTP systems are designed for capturing and processing transactions

in real time, OLAP databases are designed for reporting and analyzing data The following characteristics of OLAP structures make reporting and analysis easy to do:

! Intuitive model Data is organized in structures that are intuitive and conceptually easy to understand Users can easily retrieve information that provides a

multidimensional view of business activity—such as sales by product by

customer by region

Product, customer, and region are each a different dimension of the data, which, when combined, provide greater insight into the business activity than raw data summarized by only one dimension at a time

! Drill down and drill up Data is organized in logical hierarchies within dimensions that summarize data from low levels of detail to higher levels of summarization This

organization allows users to drill down—that is, to click through the

hierarchical layers of information—to find specific answers to questions or

format specific reports They can also drill up through the data, starting

from the lowest level moving to higher summary levels

! Slice and dice

Reporting interfaces for OLAP databases generally allow users to slice and

dice data within and between dimensions Slice and dice refers to the

capability of quickly creating reports with different dimensions and hierarchies within dimensions appearing on different row and columns axes

Pivoting is a slice and dice capability for dragging row dimension members

to a column axis and vice-versa

Topic Objective

To introduce OLAP for

reporting and analysis

Lead-in

These are the

characteristics of OLAP for

reporting and analysis

BETA MATERIALS FOR MICROSOFT CERTIFIED TRAINER PREPARATION PURPOSES ONLY

! Fast and flexible query Retrievals from an OLAP database should be fast and flexible Although OLAP is used to create static reports that are printed, analysts or managers more commonly use OLAP systems for online analysis of data where the drill down or pivoting actions take place instantly or with just a few seconds

of delay

Such online rapid querying, in which the user explores data in real time, is

frequently called ad hoc analysis, although such systems are also used for

structuring printed reports in which the rapid query capability may not be important

multidimensional data in graphical formats

! Financial applications Many different types of financial applications use OLAP databases for reporting, planning, and analysis Examples of financial applications include financial reporting, month-close analysis, product profitability analysis, budgets and forecasting, and financial modeling Financial analysts use OLAP extensively for ad hoc analysis of financial and operational data to answer questions from senior management

! Sales and marketing applications Many types of sales and marketing applications frequently use OLAP where slice and dice capabilities and timeliness of information are particularly important Examples include booking and billing applications, product analysis, customer analysis, and regional sales analysis

! Operations applications OLAP databases are adapted to a wide range of operational analyses, including manufacturing through-put and efficiency, customer service effectiveness, and product cost analysis

Topic Objective

To introduce OLAP

applications

Lead-in

OLAP databases are

adapted to a wide range of

business applications Let’s

talk about some examples

Ask students what

applications in their

organizations have been or

could be converted to an

OLAP database

BETA MATERIALS FOR MICROSOFT CERTIFIED TRAINER PREPARATION PURPOSES ONLY

OLAP in SQL Server

! Microsoft Is One of Several OLAP Vendors

! Analysis Services Is Bundled with Microsoft SQL Server 2000

! Analysis Services Include

$ OLAP engine

$ Data mining technology

OLAP technology is not unique to Microsoft Several companies distribute OLAP database engines Many companies also sell applications that provide user interfaces that interact with OLAP database engines Such applications are sometimes called client applications

Microsoft SQL Server 2000 includes two main OLAP components: the SQL Server database and Microsoft Analysis Services They are both included on the same installation media, but you can install either component without installing the other

Two distinct but overlapping tools are included in Analysis Services:

! The OLAP engine and its related components

! A data-mining tool Data mining searches for patterns in large quantities of data

For detailed information about Analysis Services and its tools, see course

2074A, Designing and Implementing OLAP Solutions with Microsoft SQL

Server 2000

Analysis Services includes multiple types of OLAP storage schemes, such as:

! Multidimensional OLAP (MOLAP) Data is stored in and retrieved from

cube structures that are separate from the relational database source of information

! Relational OLAP (ROLAP) Data is stored in and retrieved from a relational

database

! Hybrid OLAP (HOLAP) Data is stored in and retrieved from a combination

of a multidimensional cube and a relational database

Topic Objective

To introduce OLAP in SQL

Server

Lead-in

Microsoft is only one of

several OLAP vendors

Note