Designing an OLAP Solution Architecture Using MS SQL Server 2005 (M2796)

Voraussetzung:
Before attending this course, students must:
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
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.
Already know how to use:
Microsoft SQL Server Business Intelligence Development Studio
Microsoft SQL Server Management Studio
Themen:
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.
Inhalt:
Capturing Business and Technical Requirements
Capturing Business and Technical Requirements
Designing and Implementing a Logical OLAP Solution Architecture
Designing and Implementing a UDM
Designing Physical Storage for a Multidimensional Solution
Designing and Implementing Physical Storage
Creating Calculations
Implementing Calculations
Extending Cube Functionality
Implementing Advanced Functionality
Designing an Analysis Services Infrastructure
Designing and Implementing Analysis Services Infrastructure
Deploying a Multidimensional Solution into Production
Deploying Analysis Services into Production
Optimizing an OLAP Solution
Optimizing Analysis Services
Implementing Data Mining
Implementing Data Mining