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SQL Server® Analysis Services: Hands-On

Analyzing Data for Business Intelligence


Course 1394 Days

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Quick Enroll

You Will Learn How To

  • Leverage SQL Server Analysis Services to produce Business Intelligence solutions
  • Create and deploy multidimensional data cubes
  • Extend hierarchies and exploit advanced dimension relationships
  • Build custom solutions with MDX
  • Implement Key Performance Indicators (KPIs) to monitor business objectives
  • Make smarter business decisions with data mining techniques

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 to automate their maintenance using XMLA scripts and SQL Server Integration Services (SSIS) packages.

Who Should Attend

Those designing, creating or developing analysis cubes from a database. A working knowledge of relational databases is assumed.

Hands-On Training

Throughout this course, you gain extensive experience with SQL Server Analysis Services. Practical exercises include:
  • Creating and deploying a cube
  • Building aggregations with the Aggregation Design Wizard
  • Automating cube processing with an XMLA script
  • Configuring many-to-many dimension relationships
  • Implementing an action to open a Reporting Services report
  • Retrieving data using MDX
  • Discovering key influencers with data mining

Course 139 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
  • Identifying role-play dimensions
  • Adding dimension attributes and properties
  • Configuring multilanguage support

Extending the Cube with Hierarchies

Creating hierarchies

  • Building natural hierarchies and 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 MembersWithData 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, semiadditive and nonadditive measures
  • Simplifying cubes with perspectives

Managing Cubes

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 and deployment

  • Exploiting XMLA scripts and SSIS
  • Refreshing cubes with Proactive Caching
  • Deploying cubes easily through the enterprise

Performing Advanced Analysis with MDX

Retrieving data with MDX

  • Defining tuples, sets and calculated members
  • Querying cubes with MDX
  • Utilizing set functions

Monitoring business performance with KPIs

  • Building goal, status and trend expressions
  • Using PARALLELPERIOD to compare with past time periods
  • Simplifying KPI definitions using the KPIValue and KPIGoal functions

Enhancing cubes with MDX

  • Adding runtime calculations to the cube
  • Comparing MDX calculations with DSV calculated columns
  • Adding drill-through and URL actions

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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SQL Server 2008 is a registered trademark of Microsoft Corporation.
 
SQL Server Analysis Services: Hands-On

Training Dates

Live online classroom training. Participate in person or in live, online events (highlighted) via Learning Tree AnyWareTM.
Feb 14 - 17Toronto enroll
Mar 27 - 30Rockville, MD enroll
Apr 17 - 20Reston, VA enroll
Apr 24 - 27Ottawa enroll
May 15 - 18New York enroll
Jun 5 - 8Rockville, MD enroll
Jun 12 - 15Toronto enroll
Jun 19 - 22Alexandria, VA enroll
Jun 26 - 29New York enroll
Jul 24 - 27Reston, VA enroll
Aug 7 - 10New York enroll
Oct 2 - 5Rockville, MD enroll
Oct 9 - 12New York enroll
Oct 16 - 19Toronto enroll
Oct 16 - 19Alexandria, VA enroll

For AnyWare enrollments, please register at least 10 days prior to the start of the course.

More Dates and Locations.

Tuition

$ 2,890Standard Tuition
Tuition with a Savings Plan
$ 1,700Premium-Pass
$ 1,833Training Passport
$ 2,250Voucher 10-Pack
$ 2,267Triple-Pack
$ 2,573Government Discount
$ 2,600Alumni Gold Discount

On-Site &
Custom Training

Bring this or any Learning Tree course to your location or have it customized for your organization.

SQL Server Analysis Services: Hands-On

Participants creating a KPI with Business Intelligence Development Studio.


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