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You Will Learn How To
Leverage SQL Server 2005 Analysis Services to produce Business Intelligence solutions
Create cubes as part of a multidimensional data warehouse
Extend hierarchies and formulate queries with Multidimensional Expressions (MDX)
Perform administrator tasks for backing up, restoring and monitoring cubes
Make smarter business decisions with data mining techniques
Implement Key Performance Indicators (KPIs) to monitor business objectives
Course Benefits With the current explosion of data in today's enterprise environment, traditional methods of querying and reporting on information are no longer sufficient. This course provides the skills to analyse and discover trends in your data warehouse. You learn to create On-Line Analytical Processing (OLAP) cubes using Business Intelligence tools while producing an intelligent business strategy for your organisation.
Who Should Attend Business analysts and others who need to analyse data stored in SQL Server databases. A basic knowledge of relational databases is assumed.
Hands-on Training Throughout this course, you gain extensive experience with SQL Server 2005 Analysis Services. Practical exercises include:
Building a data source view
Creating and deploying a cube
Modifying cube dimensions
Navigating hierarchies
Establishing relationships in the data model
Building complex expressions with MDX
Implementing a security policy
Forecasting trends with data mining techniques
Course Content
Introduction to Business Intelligence (BI)
Defining the business needs
Creating an end-to-end solution with BI wizards
BI Studio for Analysis Services
Pulling data from disparate sources
Building and Modifying an OLAP Cube Defining fact tables
Identifying and selecting available measures
Denormalising techniques
Creating dimensions
Implementing a Star and Snowflake Schema
Calculating time dimensions with the BI Wizard
Partitioning for optimal performance
Choosing between ROLAP, MOLAP and HOLAP
Configuring incremental updates
Creating cube perspectives
Filtering business-related information
Slicing and dicing data
Extending the Cube with Hierarchies Parent-child relationships
Declaring hierarchies
Grouping related attributes
Equal Areas
Clusters
Buckets
Creating hierarchies
Modifying existing attributes
Editing grouping properties
Expanding the BI Data Model Referencing relationships
Converting a dimension to a measure
Choosing between dimension data and fact table data
Resolving many-to-many relationships
Identifying relationship anomalies
Implementing intermediate fact and dimension tables
Traversing the Hierarchies with MDX Retrieving data with MDX
Composing simple MDX queries
Manipulating data
Navigating hierarchies with parent, child, cousin and ancestor