SQLSoft Course MS-2796 Designing an Analysis Solution Architecture Using Microsoft SQL Server 2005 Analysis Services
Table of Contents
Introduction
Audience
At Course Completion
Prerequisites
Microsoft Certified Professional Exams
Student Materials
Course Outline
Introduction
The purpose of this 3-day course is to teach Business Intelligence (BI) professionals
working in enterprise environments 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.
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Audience
This course is intended for experienced BI professionals. The target students for this course already have an understanding of how to use the SQL Server 2005 tools to implement BI functionality, and have used them to build, query and maintain cubes but need to develop their understanding of design principles and best practices when planning, implementing, and deploying an Analysis Services solution.
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At Course Completion
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. |
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Prerequisites
It is critical that students have built, deployed and queried cubes using SQL Server 2005.
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. 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. |
| • |
Conceptual understanding of OLAP technologies, multi-dimensional
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 a 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 |
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Microsoft Certified Professional Exams
This course will help the student prepare for the following Microsoft Certified
Professional exams:
| • |
Exam 70-446 PRO: Designing a Business Intelligence Infrastructure by Using Microsoft SQL Server 2005 |
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Student Materials
The student kit includes a comprehensive workbook and other necessary materials
for this class.
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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 you define 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 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:
| • |
Describe the purpose of a multidimensional solution. |
| • |
Identify requirements and constraints when designing
a multidimensional solution. |
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 a Unified Dimensional Model |
| • |
Designing and Implementing Fact and Dimension Tables |
| • |
Designing and Implementing Cubes |
Lab 2: Designing and Implementing a UDM
| • |
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 a UDM 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 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
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 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
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 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
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 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
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 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
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 8: Optimizing Analysis Services
| • |
Monitoring Analysis Services |
| • |
Optimizing the Relational Database |
| • |
Optimizing Queries |
After completing this module, students will be able to:
| • |
Monitor Analysis Services. |
| • |
Optimize Analysis Services performance. |
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 5: 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. |
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