Microsoft 2074 - Designing and Implementing OLAP
Solutions with Microsoft SQL Server 2000Pré-requisitos
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.Conteúdo Programático
About this Course
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.
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.
About this CourseThis course provides students with the knowledge and skills necessary to design, implement, and deploy OLAP solutions by using Microsoft SQL Server 2000 Analysis Services.
At Course CompletionAt 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.
Module 1: Introduction to Data Warehousing and OLAP
•Introducing Data Warehousing
•Defining OLAP Solutions
•Understanding Data Warehouse Design
•Understanding OLAP Models
•Applying OLAP Cubes
Module 2: Introducing Analysis Manager Wizards
•Previewing Analysis Manager
•Preparing to Create a Cube
•Building the Sales Cube
•Processing the Cube
•Viewing the Results
Module 3: Understanding Analysis Services Architecture
•Microsoft Data Warehousing Overview
•Analysis Services Components
•Cube Storage Options
•Office 2000 OLAP Components
Module 4: Building Dimensions Using the Dimension Editor
•Understanding Dimension Basics
•Shared vs. Private Dimensions
•Working with Standard Dimensions
•Basic Level Properties
•Working with Parent-Child Dimensions
Module 5: Using Advanced Dimension Settings
•Working with Levels and Hierarchies
•Working with Time Dimensions
•Creating Custom Rollups
•Introducing Member Properties
•Understanding Virtual Dimensions
Module 6: Working with Cubes and Measures
•Introduction to Cubes
•Working with Cubes
•Introduction to Measures
•Working with Measures
•Defining Cube Properties
•Using the Disabled Property
Module 7: Case Study - Creating the Store Expense Cube
•Building the Store Expense Cube
•Updating the Store Expense Cube
Module 8: Managing Storage and Optimization
•Analysis Server Cube Storage
•The Storage Design Wizard
•Analysis Server Aggregations
Module 9: Processing Dimensions and Cubes
•Introducing Dimension and Cube Processing
•Optimizing Cube Processing
•Troubleshooting Cube Processing
Module 10: Managing Partitions
•Using Advanced Settings
Module 11: Implementing Calculations Using MDX
•Understanding Calculated Members
•Building Calculated Members
•Creating Non-Measure Calculated Members
•Using Functions Within Calculated Members
•Understanding Other Calculation Methods
•Introducing Solve Order
Module 12: Working with Virtual Cubes
•Understanding Virtual Cubes
•Obtaining Logical Results
•Building a Virtual Cube
•Creating Calculated Members
Module 13: Using Excel as an OLAP Client
•Office 2000 OLAP Components
•Using Excel PivotTables
•Working with Local Cubes
•Creating OLAP-Enabled Web Pages
Module 14: Using Actions, Drillthrough, and Writeback
Module 15: Implementing Security
•Introducing Analysis Services Security
•Understanding Administrator Security
•Helping Protect User Authentication
•Understanding Database Roles
•Implementing Dimension Security
•Managing Cube Roles
Module 16: Deploying an OLAP Solution
•Executing and Scheduling Packages
•The Analysis Services Processing Task
•Copying and Archiving OLAP Databases
Module 17: Introduction to Data Mining
•Introducing Data Mining
•Training a Data Mining Model
•Building a Data Mining Model with OLAP Data
•Browsing the Dependency Network
Module 18: Case Study - Working with the Foodmart Database
•Building the Warehouse Cube
•Building the Sales Cube
•Building the Warehouse and Sales Virtual Cube