Designing and Implementing OLAP Solutions Using Microsoft SQL Server
This course provides students with the knowledge and skills necessary to design, implement, and deploy OLAP solutions by using 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 upon 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 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, drill-through, and write-back 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 upon end-user requirements.
Prerequisites
Basic understanding of database design, administration, and implementation concepts.
Course Outline
Module 1: Introduction to OLAP and Data Warehousing
Why Data Warehousing
Understand OLAP (online analytical processing) and data warehousing concepts and applications
Data Marts and Data Warehouses
Intorduction to OLAP
Understanding Multidimensionality
The Microsoft Data Warehouse Solution
Module 2: Designing Multidimensional Data Marts
Designing a Data Warehouse Strategy
Introducing the Data Warehouse
The Relational Schema Behind the OLAP Database
OLAP and Relational Dimensions
Cubes and Fact Tables
Module 3: Previewing OLAP Using Analysis Services
Analysis Server Basics
Using OLAP Manager
Understanding the Star Schema Source
Creating the Sales Cube
Building the Sales Cube
Building the Dimensions
Finalizing the Cube
Designing Storage and Processing
Viewing the Results
Module 4: Understanding Analysis Services Architecture
Microsoft Data Warehousing Overview
Analysis Services Architecture
Storage Modes
Partitioning
Dimension Alternatives
Large Dimension Support
Caching and Write-Back
How Databases Are Organized
Other Server Side Elements
Client Architecture
Office OLAP Components
Data Mining
Module 5: Setting Up Dimensions
Understanding Dimension Basics
Private Versus Shared Dimensions
Working with Star Schema Dimensions
Working with Snowflake Dimensions
Working with Time Dimensions
Working with Parent-Child Dimensions
Creating Time Dimensions
Understand when to use shared and private dimensions.
Open and work with the dimension editor.
Add levels to dimensions.
Create dimensions from star and snowflake schemas.
Define member properties at dimension levels.
Implement time hierarchies and dimensions.
Organize levels within dimensions for drill up and drill down.
Develop parent-child dimensions.
Module 6: Advanced Dimension Settings
Creating Custom Hierarchies
Nuances of Levels
Hierarchies and Dimensions
Understanding Virtual Dimensions
Creating Cube with Financial Accounts
Creating Cube with Large Dimensions
Creating Cube with Forecasting Data
Validating and Optimizing the Cube Structure
Use the Dimension Editor and Dimension Wizard to build and fine-tune dimensions.
Make use of various dimension properties.
Work with dimension levels and hierarchies.
Create virtual dimensions from member properties.
Create custom member and rollup formulas.
Manage very large, flat dimensions.
Disable levels of a shared dimension.
Module 7: Advanced Data Mart Design Techniques
Sharing Dimensions Among Cubes With Different Granularity
Handling Nulls In the Source Data
Managing Slowly Changing Dimensions
Implementing Summary Fact Tables
Managing Various Dimension Scenarios
Optimization Tuning
Apply advanced OLAP dimension and cube design techniques.
Share dimensions across cubes with different granularity using relational and multidimensional design techniques.
Handle nulls in the source data using relational and multidimensional design techniques.
Manage slowly changing dimensions using relational and multidimensional design techniques.
Implement summary fact tables.
Module 8: Cubes and Measures
Understanding Cube Basics
Working with Cubes
Working with Measures
Defining Measure Properties
Creating Calculations
Defining Dimension Properties
Create cubes by using the Cube Editor
Add and delete measures from a cube
Add and delete dimensions from a cube
Set up a measure by using each of the five aggregation functions
Format measures
Define an internal measure
Create simple calculated members
Administer dimension properties within the Cube Editor
Module 9: Creating the Sales Reporting Cube
Building the Sales Reporting Cube
Modifying the Sales Reporting Cube
Create a cube based upon end-user requirements.
Build dimensions given the dimension tables and expected levels.
Use various dimension types.
Use expressions to create dimension member names.
Create measures.
Build simple calculated members.
Design aggregations and process the cube.
Verify cube results by using the Cube Browser.
Module 10: Virtual Cubes
Understanding Virtual Cubes
Obtaining Logical Results
Building a Virtual Cube
Creating Calculated Members
Understand when to use virtual cubes and know their benefits.
Understand the limitations of using virtual cubes.
Know the rules for constructing meaningful virtual cubes.
Build virtual cubes by using the Virtual Cube Wizard.
Define calculated members in virtual cubes by using the Calculated Member Builder.
Module 11: Storage Optimization
Analysis Server Storage
Analysis Server Aggregations
The Storage Design Wizard
Aggregation Details
Usage-Based Optimization
Optimization Tuning
Explain the pros and cons of the three data storage modes.
Describe how aggregations work.
Use the Storage Design Wizard to set storage design.
Design aggregations for cubes.
Describe the contents of a single aggregation.
Describe the concepts and mechanics of usage-based optimization.
Override aggregation settings per dimension.
Module 12: Processing Dimensions and Cubes
Overview of Schema and Data
Processing Dimensions
Rebuilding Dimensions
Incrementally Updating a Dimension
Processing Cubes
The Full Process
Refreshing a Cube
Incrementally Updating a Cube
Troubleshooting Cube Problems
Optimizing Cube Processing
Rebuild shared dimensions.
Handle new and deleted members.
Understand the difference between rebuilding and incrementally updating dimensions.
Process a cube using the three methods.
Explain the implications of the three cube processing types.
Perform an incremental data load using a database filter.
See how changes are reflected in OLAP cubes after changing data within the source RDBMS.
Module 13: Creating Partitions
Partitioning Overview
Creating Partitions
Fact Table Considerations
Working with Partitions
Merging Partitions
Explain the benefits of partitioning.
Describe the pros and cons of portioning source fact tables.
Describe the mechanics of the Partition Wizard.
Explain when to define slices and when to define filters.
Describe the purpose and mechanics of merging partitions.
Module 14: Implementing Calculations Using MDX
Understanding Calculated Members
Defining Calculated Members
Members, Tuples, and Sets
Calculated Members in Non-Measure Dimensions
Using Functions Within Calculated Members
Understanding Solve Order
Describe how calculated members work.
Describe the impact of calculated members on cube size and performance.
Explain the mechanics of the Calculated Member Builder.
Build simple calculated members.
Understand the importance of calculation solve order.
Module 15: Using Excel as an OLAP Client
Overview of Office OLAP
Creating an Excel PivotTable
Fine Tuning PivotTables
Working with PivotCharts
Working with Local Cubes
Creating OLAP Enabled Web Pages
Create a PivotTable from an OLAP cube
Interact with a PivotTable through pivots, drill-downs, and filters
Perform PivotTable formatting
Create PivotCharts
Create local cube files
Create Web pages containing Pivot web components
Module 16: Introduction to Data Mining
Understanding Data Mining
Creating A Decision Tree Model Using OLAP Data
Creating a Decision Tree Model Using Relational Data
Editing an Existing Model
Creating a Clustering Model Using OLAP Data
Creating a Clustering Model Using Relational Data
Define data mining.
Understand how data mining fits within OLAP and the Microsoft data warehousing framework.
Describe the decision tree and clustering algorithms.
Use data mining to discover data patterns.
Segment data by using data mining.
Create a data mining model using the decision tree algorithm.
Edit an existing model.
Explore the decision tree and look for predictable indicators in the results.
Module 17: Analyzing Data with Actions, Drill-Through, and Write-Back
Understanding Actions
Creating Actions
Drill-Through Fundamentals
Enabling Drill-Through
Cube Write-Back
Create and manage actions
Invoke an action that was already created
Enable cube drill-through
Understand the mechanics of cube drill-through
Set up a cube for write-back
Module 18: Implementing OLAP Security
Analysis Services Security Overview
Using Windows Security
Managing Roles
Using Virtual Cubes for Security
Defining Dimension Security
Administering Cell Level Security
Understand how Analysis Services security is linked to Windows 2000 security
Add a security role to a database via the Analysis Manager
Assign roles to a cube
Implement dimension security
Develop cell-level security by using simple MDX
Module 19: Deploying an OLAP Application
DTS Overview
Executing and Scheduling Packages
Analysis Services Processing Task
Database Migration and Disaster Recovery
Describe the role of Data Transformation Services (DTS) within OLAP applications
Create a DTS Package
Define an Analysis Services processing task
Schedule the processing of an OLAP dimension or cube
Move from testing to production environments
Perform disaster recovery on OLAP databases
Module 20: Creating the Warehouse Database
Building the Warehouse Cube
Building the Sales Cube
Building the Warehouse and Sales Virtual Cube
Deploying the Warehouse and Sales Cubes
Create cubes and virtual cubes based upon end-user requirements
Build dimensions given the dimension tables and expected levels
Create partitions by using different fact tables
Use various dimension types
Build calculated members