Introduction
Reporting and analysis applications are become more and more important in
today's business applications. Queries that aggregate over a large portion of
the data in a relational database slow down this database. Therefore, OLAP
(OnLine Analytical Processing) cubes have been invented to provide performant
aggregation querying over large amounts of data. In this course, you learn how
to build, maintain and query OLAP cubes with Microsoft Analysis Services 2008,
as well as build, maintain and query Analysis Services data mining models,
which are aimed at discovering complex, unknown and useful patterns in large
amounts of historical data.
At Course
Completion
Student will be able to create and manage Analysis Services cubes, using
features such as translations, Key Performance Indicators and calculated
members. They will be able to process cubes, design aggregations, decide upon
which type of storage is optimal. They can also setup data mining models,
process and analyse these models, and know how to create PREDICTION JOIN queries
for client side querying of these models.
Prerequisites
Students taking this course should have a basic knowledge of the SQL Server 2005
or 2008 relational database and be able to use Management Studio
The course materials, lectures, and activities are in English. To benefit
fully from the instruction, students need an understanding of the English
language and completion of the prerequisites.
Course Outline
Module 1:
Introduction
- The need for Analysis Services
- Business Intelligence in SQL Server
- Business Intelligence Development Studio
Module 2: Loading the relational
data
- Data Sources and Impersonation
- Data Source Views
- Exploring the data
Module 3: Building and deploying
basic cubes
- The auto build wizard
- Inspecting the meta-data
- Deploying cubes
- Processing cubes
Module 4: Browsing the
data
- Browsing from within Visual Studio
- Browsing from within Management Studio
- Browsing from Excel
- Browsing with Reporting Services
Module 5: Aggregation
design
- MOLAP, ROLAP and HOLAP
- Creating aggregations
- Usage based aggregation design
- Pro-active caching
- Partitioning the cube
Module 6: Processing Cubes and
Dimensions
- Different types of processing
- Processing dimensions
- Processing cubes
Module 7: Multi-Dimensional
Expressions (MDX)
- MDX expressions and queries
- Calculated members
- Adding Business Intelligence
Module 8: Key Performance Indicators
(KPI)
- What are KPIs
- Designing KPIs
- Using the KPI browser
Module 9:
Translations
- Dimension translations
- Cube translations
- Testing translated cubes
Module 10:
Actions
- Types of actions
- Creating Actions
- Using Actions
Module 11:
Perspectives
- The need for perspectives
- Creating perspectives
- Browsing perspectives
Module 12: Special
dimensions
- Different types of dimensions
- Many-to-many dimensions
- Other types of dimensions
Module 13: Data Mining
Introduction
- Why haystacks are hard to find
- Data mining skills
- Different types of data mining
Module 14: Creating data mining
models
- Create Mining Structure
- Create multiple mining models
- Deploy and process a model
- Browsing and interpreting mining models
- Testing the quality of mining models
Module 15:
Administration
- Installing Analysis Services
- Migrating AS2000 and AS2005 cubes
- Backup and Restore
- Securing Analysis Services
|