Training

• BusinessObjects™ Data Integrator XI 3.0/3.1 enables you to integrate disparate data sources to deliver more timely and accurate data that end users in an organization can trust.
• In this one-day course, you will learn about using transforms to change the structure and formatting of data, and capturing changes in data.
• As a business benefit, by being able to create efficient data integration projects, you can use the transformed data to help improve operational and supply chain efficiencies, enhance customer relationships, create new revenue opportunities, and optimize return on investment from enterprise applications.
  

• Describe the Data Integrator transforms
• Use the Pivot transform
• Use the Hierarchy Flattening transform
• Describe performance optimization
• Use the Data Transfer transform
• Use the XML Pipeline transform

• Describe the options for updating changes to data
• Explain the purpose of Changed Data Capture (CDC)
• Explain the roles of surrogate keys in managing changes to data
• Use and define the differences between source-based and target- based CDC

Essential
To be successful, learners who attend this course must have taken the following:

• Knowledge of data warehousing and ETL concepts
• Experience with MySQL and SQL language
• Experience using functions, elementary procedural programming, and flow-of-control statements such as If-Then-Else and While Loop statements
• Data Warehouse Fundamentals: TCO Starts with the End User and Fact Tables and Dimension Tables
• Data Warehouse Architecture and Modeling: There Are No Guarantees
• Advance Dimension Table Topics: Surrogate Keys,It's Time for Time, and Slowly Changing Dimensions
• Industry- and Application-Specific Issues: Think Globally, Act Locally
• Data Staging and Data Quality: Dealing with Dirty Data
• It is also recommended you review the following articles, which can be found at: http://www.rkimball.com/html/articles.html .
• Data Warehouse Fundamentals: TCO Starts with the End User and Fact Tables and Dimension Tables
• Data Warehouse Architecture and Modeling: There Are No Guarantees
• Advance Dimension Table Topics: Surrogate Keys,It's Time for Time, and Slowly Changing Dimensions
• Industry- and Application-Specific Issues: Think Globally, Act Locally
• Data Staging and Data Quality: Dealing with Dirty Data