Designing an analysis solution architecture using Microsoft SQL Server 2005 Analysis Services (MOC 2796)

Special note

Consider taking this course, HE581S (MOC 2796) along with course HE579S (MOC 2794). Both are scheduled together in the same week.

Course overview

The purpose of this 3-day course is to teach business intelligence (BI) professionals working in enterprise environments how to design a multidimensional solution architecture that supports their BI solution. Students will go through the entire process-from capturing business and technical requirements, to deploying a multidimensional solution, to production. Students will also be taught to develop custom functionality and optimize a multidimensional solution.

The course focuses on the planning and design aspects of an analysis solution and does not teach students how to create Analysis Services database objects or how to use the development tools provided with SQL Server 2005.

Prerequisites

• Have hands-on experience with database development tasks. For example:
  • Creating Transact-SQL queries
  • Writing and optimizing advanced queries (for example, queries that contain complex joins or subqueries)
  • Creating database objects such as tables, views, and indexes
  • Have foundational conceptual understanding of data warehousing, data marts, and business intelligence. Students must be well versed on the subjects of data warehousing, data marts, and BI, and preferably have read at least one book by Ralph Kimball or Bill Inmon
  • Have a conceptual understanding of OLAP technologies, multidimensional data, MDX, and relational database modeling. For example, know what facts, dimensions, measures, calculated measures, and foreign keys are
  • Be familiar with SQL Server 2005 features, tools, and technologies. In particular, they must have built and queried an Analysis Services cube
  • Have foundational understanding of Microsoft Windows security. For example, how groups, delegation of credentials, and impersonation function in a security context
  • Have foundational understanding of Web-based architecture. For example, SSL, SOAP, and IIS-what they are and what their role is
  • Must understand the difference between replication and ETL
• Already know how to use:
  • Microsoft Office Visio
  • Microsoft SQL Server Business Intelligence Development Studio
  • Microsoft SQL Server Management Studio
  • Performance Monitor
  • Microsoft SQL Server Profiler

Audience

Ways to save

Benefits to you

After completing this course, students will be able to:

• Capture the business and technical requirements for a BI solution
• Design and implement a logical Online Analytical Processing (OLAP) solution architecture
• Design physical storage for a multidimensional solution
• Create calculated members and named sets
• Implement Key Performance Indicators (KPIs), actions, and stored procedures
• Design the infrastructure for an OLAP solution
• Deploy and secure an Analysis Services solution in a production environment
• Monitor and optimize an Analysis Services solution
• Implement a Data Mining Solution

Course outline

Module 1: Capturing Business and Technical Requirements

Lessons

• Planning a Multidimensional Solution
• Identifying Requirements and Constraints

Lab 1: Capturing Business and Technical Requirements

• Reviewing Solution Requirements
• Identifying Further Information Requirements

After completing this module, students will be able to:

• Plan an analysis solution
• Identify requirements and constraints when designing an analysis solution

Module 2: Designing and Implementing a Logical OLAP Solution Architecture

Lessons

• Planning an OLAP Solution
• Designing and Implementing Fact and Dimension Tables
• Designing and Implementing Cubes

Lab 2: Designing and Implementing an OLAP Solution

• Designing and Implementing a Relational Database Schema
• Designing and Implementing a Cube
• Designing and Implementing Perspectives

After completing this module, students will be able to:

• Describe design considerations for an OLAP solution
• Describe design considerations for the relational schema of an OLAP solution
• Describe considerations for designing and implementing OLAP cubes

Module 3: Designing Physical Storage for a Multidimensional Solution

Lessons

• Designing Physical Storage
• Partitioning Relational Data
• Partitioning Multidimensional Data

Lab 3: Designing and Implementing Physical Storage

• Designing and Implementing a Storage Solution
• Designing and Implementing Relational Partitioning
• Designing and Implementing Multidimensional Partitioning
• Testing the Solution

After completing this module, students will be able to:

• Design an effective physical storage solution for dimensions and measures
• Partition relational data
• Partition multidimensional data

Module 4: Creating Calculations

Lessons

• Implementing Calculated Members
• Implementing Named Sets
• Implementing Scoped MDX Scripts

Lab 4: Implementing Calculations

• Creating Calculated Members
• Creating Named Sets
• Creating a Scoped MDX Script

After completing this module, students will be able to:

• Create calculated members
• Create named sets
• Create scoped assignments

Module 5: Extending Cube Functionality

Lessons

• Key Performance Indicators
• Actions
• Stored Procedures

Lab 5: Implementing Advanced Functionality

• Creating KPIs
• Creating Actions
• Creating Stored Procedures

After completing this module, students will be able to:

• Create KPIs
• Create actions
• Create stored procedures

Module 6: Designing an Analysis Services Infrastructure

Lessons

• Considerations for Analysis Services Resource Requirements
• Considerations for Analysis Services Scalability
• Considerations for Analysis Services Availability

Lab 6: Designing and Implementing Analysis Services Infrastructure

• Planning Production System Infrastructure
• Installing Analysis Services in a Cluster

After completing this module, students will be able to:

• Specify appropriate hardware and software resources for an Analysis Services solution
• Design an Analysis Services infrastructure that supports high scalability
• Design an Analysis Services infrastructure that supports high availability

Module 7: Deploying a Multidimensional Solution into Production

Lessons

• Deploying an Analysis Services Database
• Managing Analysis Services Security

Lab 7: Deploying Analysis Services into Production

• Deploying an Analysis Services Database
• Enabling User Access

After completing this module, students will be able to:

• Deploy an Analysis Services solution
• Secure an Analysis Services solution

Module 8: Optimizing an OLAP Solution

Lessons

• Monitoring Analysis Services
• Optimizing Performance

Lab 8: Optimizing Analysis Services

• Monitoring Analysis Services
• Optimizing Queries

After completing this module, students will be able to:

• Monitor Analysis Services
• Optimize the performance of Analysis Services

Module 9: Implementing Data Mining

Lessons

• Introduction to Data Mining
• Implementing a Data Mining Solution
• Using Data Mining in a BI Solution

Lab 9: Implementing Data Mining

• Creating a Data Mining Structure
• Validating a Data Mining Structure

After completing this module, students will be able to:

• Plan a data mining solution
• Implement a data mining solution
• Use data mining in a BI solution