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Course Content
Building and Modifying an OLAP Cube
- Designing a Unified Dimension Model (UDM)
- Identifying measures and their suitable granularities
- Adding new measure groups and creating custom measures
- Creating dimensions
- Implementing a Star and Snowflake Schema
- Managing Slow Changing Dimensions (SCD)
- Identifying role-play dimensions
Extending the Cube with Hierarchies
- Creating hierarchies
- Building natural hierarchies
- Many-to-many hierarchies
- Creating attribute relationships
- Distinguishing between ragged, balanced and unbalanced hierarchies
- Discretizing attribute values with the Clusters and Equal Areas algorithms
- Parent-child relationships
- Defining parent and key attributes
- Generating level captions with the Naming Template feature
- Removing repeated entries with the Members With Data property
Exploiting Advanced Dimension Relationships
- Storing dimension data in fact tables
- Building a degenerate dimension
- Configuring fact relationships
- Saving space with referenced dimension relationships
- Identifying candidates for referenced relationships
- Utilizing the Dimension Usage tab to configure referenced relationships
- Including dimensions with many-to-many relationships
- Implementing intermediate measure groups and dimensions
- Reporting on many-to-many dimensions without double counting
Designing Optimal Cubes
- Assembling cube components
- Selecting the appropriate fact tables
- Adding cube dimensions
- Distinguishing between additive, semi-additive and nonadditive measures
- Designing storage and aggregations
- Choosing between ROLAP, MOLAP and HOLAP
- Partitioning cubes for improved performance
- Designing aggregations with the Aggregation Design Wizard
- Leveraging the Usage-Based Optimization Wizard
- Automating processing
- Exploiting XMLA scripts and SSIS
- Refreshing cubes with Proactive Caching
Performing Advanced Analysis with MDX
- Retrieving data with MDX
- Defining tuples, sets and calculated members
- Querying cubes with MDX
- Navigating hierarchies with MDX and utilizing set functions
- Monitoring business performance with KPIs
- Building goal, status and trend expressions
- Using PARALLELPERIOD to compare with past time periods
- Creating calculations with MDX
- Adding runtime calculations to the cube
- Comparing MDX calculations with DSV calculated columns
Securing Cube Data
- Securing data and simplifying the user interface
- Distinguishing between perspective feature and security
- Creating roles for administrative privileges
- Securing dimension data
- Implementing cell-level security
Gaining Business Advantage with Data Mining
- Determining the correct model
- Identifying business tasks for data mining
- Training and testing data mining algorithms
- Comparing algorithms with the accuracy chart and classification matrix
- Optimizing returns with the Profit Chart
- Performing real-world predictions
- Classifying with the Decision Trees, Neural Network and Naive Bayes algorithms
- Predicting with the Time Series algorithm
- Deploying models
- Predicting new cases with algorithms
- Utilizing DMX to perform batch and singleton predictions
- Exploring results with data mining viewers
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