3 Day Course
Introduction
Elements of this syllabus are subject to change.
The purpose of this three 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.
Audience Profile
This course is intended for experienced BI professionals. The target
students for this course already have an understanding of how to use SQL Server
2005 tools to implement Analysis Services functionality, but need to develop
their understanding of design principles and best practices when planning,
implementing, and deploying an Analysis Services solution.
At Course Completion
After completing this course, students will be able to:
•
Capture the business and technical requirements
for an analysis 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
Prerequisites
Before attending this course,
students must:
•
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
o• 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
o• For example, know what facts, dimensions,
measures, calculated measures, and foreign keys are
•
Be
familiar with SQL Server 2005 features, tools, and technologies
o• In particular, they must have built and queried
an Analysis Services cube
•
Have
foundational understanding of Microsoft Windows security
o• For example, how groups, delegation of
credentials, and impersonation function in a security context
•
Have
foundational understanding of Web-based architecture
o• 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:
o• Microsoft Office Visio
o• Microsoft SQL Server Business Intelligence
Development Studio
o• Microsoft SQL Server Management Studio
o• Performance Monitor
o• Microsoft SQL Server Profiler
Course Outline
Module 1: Capturing Business and Technical Requirements
In this module, students will
first learn about key design principles that they should consider when defining
the scope of a BI project. They will then learn how to identify the business
and technical requirements to ensure that their solution meets the needs of its
users.
Lessons
- Planning an Analysis Solution
- Identifying Requirements and Constraints
Lab: Capturing Business and Technical Requirements
- Reviewing Solution Requirements
- Identifying Further Information Requirements
Module 2: Designing and Implementing a Logical OLAP Solution
Architecture
This module describes
considerations and guidelines for designing an OLAP solution, including a
relational data warehouse and an Analysis Services cube.
Lessons
- Planning an OLAP Solution
- Designing and Implementing Fact and Dimension Tables
- Designing and Implementing Cubes
Lab: 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
In this module, students will
learn how to design an effective physical storage solution for a
multidimensional application.
Lessons
- Designing Physical Storage
- Partitioning Relational Data
- Partitioning Multidimensional Data
Lab: 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
In this module, students will
learn how to create Multidimensional Expression (MDX) calculations. The module
describes how to create calculated members, named sets, and scoped assignments.
Lessons
- Implementing Calculated Members
- Implementing Named Sets
- Implementing Scoped MDX Scripts
Lab: 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
In this module, students will
learn about the benefits of KPIs, actions, and stored procedures. They will
also learn how to implement KPIs, actions, and stored procedures in an Analysis
Services cube.
Lessons
- Key Performance Indicators
- Actions
- Stored Procedures
Lab: 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
In this module, students will
learn how to design an appropriate infrastructure for an OLAP application.
Lessons
- Considerations for Analysis Services
Resource Requirements
- Considerations for Analysis Services
Scalability
- Considerations for Analysis Services
Availability
Lab: 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
In this module, students will
learn about and compare the different deployment methods available in SQL
Server 2005 Analysis Services. They will also learn about how security in
Analysis Services functions and how to protect their company's critical
business information.
Lessons
- Deploying an Analysis Services Database
- Managing Analysis Services Security
Lab: 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
In this module, students will
learn how to monitor Analysis Services and how to optimize performance of their
Analysis Services solutions.
Lessons
- Monitoring Analysis Services
- Optimizing Performance
Lab: 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
In this module, students will
learn what a data mining solution is and how to design and implement data
mining functionality with SQL Server Analysis Services.
Lessons
- Introduction to Data Mining
- Implementing a Data Mining Solution
- Using Data Mining in a BI Solution
Lab: 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
