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MS2796 - Designing an Analysis Solution Architecture Using SQL 2005

If you have any questions about registering for this class, please call (877) 832-0688 Ext. 1493 or email us at getsmart@LRS.com
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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Prerequisites

• 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
 
Detailed Class Syllabus


Module 1: Capturing Business and Technical Requirements
  • Planning a Multidimensional Solution

  • Identifying Requirements and Constraints

  • Lab 1: Capturing Business and Technical Requirements

  • Reviewing Solution Requirements

  • Identifying Further Information Requirements


  • Module 2: Designing and Implementing a Logical OLAP Solution Architecture
  • 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


  • Module 3: Designing Physical Storage for a Multidimensional Solution
  • 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


  • Module 4: Creating Calculations
  • 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


  • Lab 5: Implementing Advanced Functionality
  • Creating KPIs

  • Creating Actions

  • Creating Stored Procedures


  • Lab 6: Designing and Implementing Analysis Services Infrastructure
  • Planning Production System Infrastructure

  • Installing Analysis Services in a Cluster


  • Module 7: Deploying a Multidimensional Solution into Production
  • Deploying an Analysis Services Database

  • Managing Analysis Services Security

  • Lab 7: Deploying Analysis Services into Production

  • Deploying an Analysis Services Database

  • Enabling User Access


  • Module 8: Optimizing an OLAP Solution
  • Monitoring Analysis Services

  • Optimizing Performance

  • Lab 8: Optimizing Analysis Services

  • Monitoring Analysis Services

  • Optimizing the Relational Database

  • Optimizing Queries


  • Module 9: Implementing Data Mining
  • Introduction to Data Mining

  • Implementing a Data Mining Solution

  • Using Data Mining in a BI Solution

  • Lab 9: Implementing Data Mining

  • Creating a Data Mining Structure

  • Validating a Data Mining Structure
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