MOC 2796 Designing an Analysis Solution Architecture Using Microsoft SQL Server 2005 Analysis Services - Seminare

Seminar-Ziel

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.

Teilnehmer Zielgruppe

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.

Kurs Voraussetzungen

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.
• 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

Seminar-Inhalt

Module 1: Capturing Business and Technical Requirements

Lessons

• Planning an Analysis Solution
• Identifying Requirements and Constraints

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

Module 3: Designing Physical Storage for a Multidimensional Solution

Lessons

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

Module 4: Creating Calculations

Lessons

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

Module 5: Extending Cube Functionality

Lessons

• Key Performance Indicators
• Actions
• 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

Module 7: Deploying a Multidimensional Solution into Production

Lessons

• Deploying an Analysis Services Database
• Managing Analysis Services Security

Module 8: Optimizing an OLAP Solution

Lessons

• Monitoring Analysis Services
• Optimizing Performance

Module 9: Implementing Data Mining

Lessons

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

Literatur

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