Building and Modifying an OLAP Cube

Course ID: CLBIAS017

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 multi language support

[accordion_item in="false" id_parent="faq" title="Extending the Cube with Hierarchies"]

  • Creating hierarchies
    • Building natural hierarchies and creating attribute relationships
    • Discretizing attribute values with the Clusters and Equal Areas algorithms
  • Parent-child relationships
    • Defining parent and key attributes
    • Generating level captions with Naming Template

[accordion_item in="false" id_parent="faq" title="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
  • Implementing a Tabular Model Database
    • Providing users with analytics via Vertipaq and Power Pivot
    • Comparing Direct Query mode and classic MDX
    • Mapping out the role of SharePoint

[accordion_item in="false" id_parent="faq" title="Managing Cubes"]

  • Designing storage and aggregations
    • Choosing between ROLAP, MOLAP and HOLAP
    • Partitioning cubes for improved performance
    • Designing aggregations with Aggregation Design Wizard
    • Leveraging the Usage-Based Optimization Wizard
  • Automating processing and deployment
    • Exploiting XMLA scripts and SSIS
    • Refreshing cubes with Proactive Caching

[accordion_item in="false" id_parent="faq" title="Performing Advanced Analysis with MDX"]

  • Retrieving data with MDX
    • Defining tuples, sets and calculated members
    • Querying cubes with MDX
  • Monitoring business performance with KPIs
    • Building goal, status and trend expressions
    • Using PARALLELPERIOD to compare past time periods
    • Simplifying KPI definitions using KPIValue and KPIGoal
  • Enhancing cubes with MDX
    • Adding runtime calculations to the cube
    • Adding drill-through and URL actions

[accordion_item in="false" id_parent="faq" title="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
  • Performing real-world predictions
    • Classifying with Decision Trees, Neural Network and Naive Bayes algorithms
    • Predicting with the Time Series algorithm

[accordion id="faq"]
[accordion_item in="true" id_parent="faq" title="What is this course about?"]
This course provides comprehensive coverage of Microsoft SQL Server Analysis Services. You learn to import and analyze data from heterogeneous sources. The numerous hands-on exercises in this course are designed to illustrate real-world problems and provide practical solutions that you can apply immediately in the workplace.[/accordion_item]
[accordion_item in="false" id_parent="faq" title="Who will benefit from this course?"]
Typically, participants who have been involved with database design and have experience with moving data between heterogeneous sources with SQL Server Integration Services will benefit from this course. Typical job titles include: data architects, business analysts, and data warehousing specialists. A basic knowledge of relational databases and Microsoft Business Intelligence tools is assumed. Experience with Microsoft Excel is assumed.
[accordion_item in="false" id_parent="faq" title="What background do I need?"]
You should have a basic knowledge of relational database management systems and the SQL language. Specific experience with Microsoft SQL Server is helpful, but not required for this course. You should also have some knowledge of basic programming concepts but specific knowledge of a particular language is not required.
[accordion_item in="false" id_parent="faq" title="Do I need to know SQL?"]
A basic knowledge of SQL is helpful but not required.
[accordion_item in="false" id_parent="faq" title="Do I need to have a statistics background?"]
No, you do not need to have a background in statistics in order to succeed in this course. Knowledge of statistics is helpful, but not required.
[accordion_item in="false" id_parent="faq" title="How much of this class is focused on scripting and/or programming?"]
Most tasks in this course can be accomplished with no programming. You learn to use programming to extend the capabilities of SSAS even if you have never programmed before. All of the necessary information to complete the exercises is given in the course.
[accordion_item in="false" id_parent="faq" title="What is the role of SSAS in Business Intelligence?"]
SSAS is one of the components in Microsoft’s Business Intelligence platform. The other two consist of SQL Server Reporting Services (SSRS) and SQL Server Integration Services (SSIS). Integration Services allows you to migrate data for decision support purposes. Once migrated, data can be analyzed with Analysis Services and reports can be built using Reporting Services
[accordion_item in="false" id_parent="faq" title="I am using Oracle as my main database platform. Will this course be helpful to me?"]
Yes! Analysis Services can be used to analyze data from virtually any source. For example, it can be used to analyze data from Sybase or Oracle.
[accordion_item in="false" id_parent="faq" title="Will I learn the MDX language?"]
Yes, there is one chapter and several exercises devoted to this topic. MDX, or Multidimensional Expressions, allows for calculations within the cube. There are some calculations that cannot be done through the GUI, and MDX provides the means to accomplish these tasks.
[accordion_item in="false" id_parent="faq" title="Why do I need to learn about Key Performance Indicators (KPIs)?"]
KPIs enable you to monitor complex business goals by comparing the indicators with the multidimensional cube data. This creates a simplified way to view business performance. There is one exercise on this topic in the course.
[accordion_item in="false" id_parent="faq" title="Will I learn how to build a cube?"]
Yes, the majority of the course is about creating, extending and presenting cubes in a user-friendly manner.
[accordion_item in="false" id_parent="faq" title="How can data mining help my organization?"]
Data mining is a method of spotting patterns and trends in data. It goes beyond simple analysis. Through the use of sophisticated algorithms, users have the ability to identify key attributes of business processes and target opportunities. Data mining enables you to predict the buying patterns of customers, detect fraud in financial transactions, and focus marketing strategies.

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