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SQL Server 2005 Analysis Services: Hands-On You Will Learn How To Leverage SQL Server 2005 Analysis Services to produce Business Intelligence solutions Create and deploy multidimensional data cubes Extend hierarchies and exploit advanced dimension relationships 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 knowledge and skills to analyze and discover trends in your data warehouse. You learn to create On-Line Analytical Processing (OLAP) cubes using Business Intelligence tools and leverage the Analysis Services administrative tools to better manage and maintain your data.   Who Should Attend Technical business analysts and others who need to analyze data stored in SQL Server databases. A working 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 Creating and using a perspective for browsing Implementing a security policy Forecasting trends with data mining techniques   Introduction to Business Intelligence (BI) Defining the business needs Creating an end-to-end solution with wizards BI Studio for Analysis Services Building data sources and views in the Unified Dimensional Model (UDM) Pulling data from disparate sources Building and Modifying an OLAP Cube Defining fact tables Identifying and selecting available measures Determining foreign key dependencies with dimensions 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 Deploying the cube to the organization Modifying dimension attributes Using dimension properties for specific needs Adding attributes to match the dimension tables Implementing stored procedures for Analysis Services Improving dimension usability Changing granularity in a measure group 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 Retrieving data with MDX Composing simple MDX queries Manipulating data Navigating hierarchies with parent, child, cousin and ancestor 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 Creating cube perspectives Filtering business-related information Slicing and dicing data Working with local languages Administering Analysis Services Implementing security Creating roles and grouping users Assigning permissions to objects Controlling data access Preventing access to data sources Giving rights to securables Performance monitoring Monitoring current activity with the profiler Caching to avoid disk access Guarding against disasters Backing up the Analysis database with Management Studio Restoring databases Synchronizing databases wizard Gaining Business Advantage with Data Mining Finding patterns in your data Correlating business trends Predicting future trends with algorithms Determining the correct model Choosing between discrete and continuous attributes Analyzing various data mining algorithms Validating models Training algorithms for optimal results Exploring results with data mining viewers Monitoring KPIs for Better Business Decisions Reporting on business objectives with KPIs Establishing business goals Selecting critical performance indicators Implementing KPIs with expressions Running reports based on Analysis Services Browsing the cube with dashboards Enumerating available client tools Viewing KPIs with SharePoint Encapsulating business trends into a single view

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