Designing and Implementing OLAP Solutions Using Microsoft SQL Server 2000

Course 2074—Five days—Instructor-led

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IntroductionIntroduction
At Course CompletionAt Course Completion
Microsoft Certification examsMicrosoft Certification exams
PrerequisitesPrerequisites
Course MaterialsCourse Materials
Course OutlineCourse Outline
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Introduction

This course provides students with the knowledge and skills necessary to design, implement, and deploy OLAP solutions by using Microsoft SQL Server 2000 Analysis Services.


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At Course Completion

At the end of the course, students will be able to:

Define the term OLAP and its role within data warehousing.

Design multidimensional data marts by using star and snowflake schemas.

Recognize the fundamental components of a cube.

Understand the architecture of Analysis Services.

Create dimensions from relational dimension tables.

Understand the many types of dimensions.

Utilize various dimension properties and settings.

Design OLAP dimensions based on underlying source data.

Create cubes by using the Cube Wizard and Cube Editor.

Create and manipulate measures.

Develop and understand virtual cubes.

Design cube storage and aggregations.

Update dimensions and cubes when source data changes.

Optimize the processing of dimensions and cubes.

Create partitions within cubes.

Implement simple calculations by using multidimensional expressions (MDX) and calculated members.

Use Microsoft Excel 2000 as an OLAP front-end application.

Understand how data mining fits within OLAP and the Microsoft data warehousing framework.

Employ actions, drillthrough, and writeback for data analysis.

Design and implement cube and dimension security.

Automate the processing of dimensions and cubes through Data Transformation Services (DTS).

Create cubes and virtual cubes based on end-user requirements.


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Microsoft Certification exams

This course will help the student prepare for the following Microsoft Certified Professional exam:

There is no MCP exam associated with this course


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Prerequisites

Before attending this course, students must have:

A basic understanding of database design, administration, and implementation concepts.

A satisfactory level of comfort within the Microsoft Windows 2000 environment.


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Course Materials

The course materials are yours to keep.

The following software is provided for use in the classroom:

Microsoft SQL Server 2000

Microsoft Excel 2000


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Course Outline



Module 1: Introduction to Data Warehousing and OLAP

The following topics are covered in this module:

Introducing Data Warehousing

Defining OLAP Solutions

Understanding Data Warehouse Design

Understanding OLAP Models

Applying OLAP Cubes

At the end of this module, you will be able to explain the basic design of an OLAP solution. This includes:

Describing characteristics, goals, and applications of a data warehouse.

Understanding the need and use for OLAP solutions.

Describing data warehouse design.

Understanding the reasons for implementing OLAP models and describing their components.

Visualizing a multidimensional database.

Module 2: Introducing Analysis Manager Wizards

The following topics are covered in this module:

Defining Terms

Previewing Analysis Manager

Preparing to Create a Cube

Building the Sales Cube

Processing the Cube

Viewing the Results

At the end of this module, you will be able to use the Analysis Manager tools to create and process a cube. This includes:

Describing Analysis Services components.

Navigating through the basic interfaces of Analysis Manager.

Preparing to create a cube by reviewing data sources and initiating the Cube Wizard.

Creating an OLAP cube by using the Cube and Dimension Wizards.

Processing a cube.

Browsing the cube data and metadata by using the Analysis Manager browser.

Module 3: Understanding Analysis Services Architecture

The following topics are covered in this module:

Overview

Microsoft Data Warehousing Overview

Analysis Services Components

Metadata Repository

Cube Storage Options

Client Architecture

Office 2000 OLAP Components

At the end of this module, you will be able to explain the integration and interaction of the Analysis Services components. This includes:

Describing the components of the Microsoft data warehouse strategy.

Understanding the Analysis Services components.

Describing the function of the Microsoft Metadata Repository.

Explaining the basic differences between the three storage modes for OLAP cubes-multidimensional OLAP (MOLAP), relational OLAP (ROLAP), and hybrid OLAP (HOLAP).

Understanding client architecture and the role of the Microsoft PivotTable Service.

Recognizing Microsoft Office 2000 OLAP capabilities.

Module 4: Building Dimensions Using the Dimension Editor

The following topics are covered in this module:

Understanding Dimension Basics

Shared vs. Private Dimensions

Working with Standard Dimensions

Basic Level Properties

Working with Parent-Child Dimensions

At the end of this module, you will be able to build dimensions by using the Dimension Editor. This includes:

Understanding dimension fundamentals.

Knowing when to use shared and private dimensions.

Describing the characteristics of standard dimensions.

Adding level properties to dimensions.

Developing parent-child dimensions.

Module 5: Using Advanced Dimension Settings

The following topics are covered in this module:

Working with Levels and Hierarchies

Working with Time Dimensions

Creating Custom Rollups

Introducing Member Properties

Understanding Virtual Dimensions

At the end of this module, you will be able to use various advanced dimension settings and methods to develop OLAP dimensions and cubes. This includes:

Working with dimension levels and hierarchies.

Understanding and working with time dimensions.

Creating custom rollup dimensions.

Defining member properties at dimension levels.

Creating virtual dimensions from member properties and member levels.

Module 6: Working with Cubes and Measures

The following topics are covered in this module:

Introduction to Cubes

Working with Cubes

Introduction to Measures

Working with Measures

Defining Cube Properties

Using the Disabled Property

At the end of this module, you will be able to use the Cube Editor to create and manipulate cubes, add measures and dimensions, and assign properties to improve cubes. This includes:

Defining the required components of cubes.

Creating cubes by using the Cube Editor.

Describing the characteristics of measures.

Assigning properties to measures.

Modifying cube properties by using the Cube Editor.

Disabling levels of shared dimensions.

Module 7: Case Study - Creating the Store Expense Cube

The following topics are covered in this module:

Building the Store Expense Cube

Updating the Store Expense Cube

At the end of this module, you will be able to create a preliminary cube and make changes to the cube by applying dimension and level properties. This includes:

Creating a cube based on user requirements.

Updating dimensions and adding new dimensions to a cube.

Module 8: Managing Storage and Optimization

The following topics are covered in this module:

Analysis Server Cube Storage

The Storage Design Wizard

Analysis Server Aggregations

Usage-Based Optimization

Optimization Tuning

At the end of this module, you will be able to make choices of storage options and optimizations for OLAP cubes. This includes:

Explaining the advantages and disadvantages of the three data storage models.

Using the Storage Design Wizard to set storage design.

Describing how aggregations work and designing aggregations for cubes.

Describing the concepts and mechanics of usage-based optimization.

Overriding aggregation settings per dimension.

Module 9: Processing Dimensions and Cubes

The following topics are covered in this module:

Introducing Dimension and Cube Processing

Processing Dimensions

Processing Cubes

Optimizing Cube Processing

Troubleshooting Cube Processing

At the end of this module, you will be able to manage dimension and cube processing. This includes:

Understanding the difference between OLAP schema and data.

Processing dimensions.

Performing the three types of cube processes.

Obtimizing cube processing.

Troubleshooting cube processing.

Module 10: Managing Partitions

The following topics are covered in this module:

Introducing Partitions

Creating Partitions

Using Advanced Settings

Merging Partitions

At the end of this module, you will be able to use partitions to improve both processing and query performance. This includes:

Explaining the benefits of partitioning.

Describing the mechanics of the Partition Wizard

Explaining when to define slices and when to define filters.

Describing the purpose and mechanics of merging partitions.

Module 11: Implementing Calculations Using MDX

The following topics are covered in this module:

Understanding Calculated Members

Building Calculated Members

Creating Non-Measure Calculated Members

Using Functions Within Calculated Members

Understanding Other Calculation Methods

Introducing Solve Order

At the end of this module, you will be able to begin working with calculated members and multidimensional expressions (MDX). This includes:

Describing how calculated members work.

Explaining the mechanics of the Calculated Member Builder and creating calculated members.

Creating calculated members in non-Measure dimensions.

Understanding the use of functions in calculated members.

Understanding other calculation methods in Analysis Services.

Understanding the importance of Solve Order to generate accurate results.

Module 12: Working with Virtual Cubes

The following topics are covered in this module:

Understanding Virtual Cubes

Obtaining Logical Results

Building a Virtual Cube

Creating Calculated Members

At the end of this module, you will be able to build and use virtual cubes. This includes:

Understanding when to use virtual cubes and knowing their benefits.

Knowing the rules for constructing meaningful virtual cubes.

Building virtual cubes by using the Virtual Cube Wizard.

Defining calculated members in virtual cubes by using the Calculated Member Builder.

Module 13: Using Excel as an OLAP Client

The following topics are covered in this module:

Office 2000 OLAP Components

Using Excel PivotTables

Using PivotCharts

Working with Local Cubes

Creating OLAP-Enabled Web Pages

At the end of this module, you will be able to use various Office 2000 OLAP features. This includes:

Understanding the various Microsoft Office 2000 OLAP features.

Creating a PivotTable from an OLAP cube.

Creating PivotCharts

Creating local cube files

Creating a Web page containing Pivot Web components.

Module 14: Using Actions, Drillthrough, and Writeback

The following topics are covered in this module:

Creating Actions

Performing Drillthrough

Understanding Writeback

At the end of this module, you will be able to use these three features to add layers of analysis to OLAP applications. This includes:

Creating and viewing actions.

Implementing and testing drillthrough.

Understanding the applications for cube writeback.

Module 15: Implementing Security

The following topics are covered in this module:

Introducing Analysis Services Security

Understanding Administrator Security

Helping Protect User Authentication

Understanding Database Roles

Implementing Dimension Security

Managing Cube Roles

At the end of this module, you will be able to implement security in Analysis Services. This includes:

Understanding the uses of security in Analysis Services.

Explaining adminstrator security.

Describing authentication methods.

Assigning database roles.

Applying dimension security.

Managing cube roles.

Module 16: Deploying an OLAP Solution

The following topics are covered in this module:

Introducing DTS

Executing and Scheduling Packages

The Analysis Services Processing Task

Copying and Archiving OLAP Databases

At the end of this module, you will be able to automate various steps in the deployment of an OLAP solution. This includes:

Describing the role of Data Transformation Services (DTS).

Creating a DTS package.

Defining an Analysis Services processing task.

Copying, archiving, and restoring OLAP databases.

Module 17: Introduction to Data Mining

The following topics are covered in this module:

Introducing Data Mining

Training a Data Mining Model

Building a Data Mining Model with OLAP Data

Browsing the Dependency Network

At the end of this module, you will be able to explain and use simple data mining techniques. This includes:

Describing data mining characteristics, applications, and modeling techniques.

Describing the process of training a model.

Using the OLAP Mining Model Wizard to edit, process, and explore the decision trees.

Analyzing relational data relationships in the dependency network browser.

Describing the steps required to build a clustering model by using OLAP data.

Module 18: Case Study - Working with the Foodmart Database

The following topics are covered in this module:

Building the Warehouse Cube

Building the Sales Cube

Building the Warehouse and Sales Virtual Cube

At the end of this module, you will be able to demonstrate the ability to create a preliminary cube and then make changes to it by applying dimension and level properties. This includes:

Creating a cube based on user requirements.

Creating another cube with different dimensions and measures.

Building a virtual cube.

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