Undergraduate Admission
    Graduate Admission

    Data Warehousing, IT 526

    About this Course:
    This class will introduce the student to concepts needed for successfully designing, building and implementing a data warehouse. The class will provide the technological and managerial knowledge base for data modeling approaches such as the star schema and database de-normalization issues. Topics such as loading the warehouse, performance considerations, and other concepts unique to the data warehouse environment will be discussed demonstrated in detail.

    Currently Scheduled

    IT 421 Database Concepts with Oracle or experience with relational databases and familiarity with basic programming concepts and SQL are required for enrollment.

    Who Should Attend:
    Professionals interested in learning data warehouse concepts and implementation.

    Expected Outcomes:

    After the successful completion of this course, participants will be able to,

    • Explain top down and bottom up approaches for building data warehouses
    • Correctly use data warehouse and business intelligence terminologies
    • Apply business dimensional lifecycle
    • Perform multidimensional analysis
    • Describe techniques of data warehouse technical architecture
    • Demonstrate techniques for building a dimensional data mart/warehouse.
    • Determine the need for and management of meta data.

    Course Outline:

    Introduction to Business Intelligence and Corporate Information

    Information to the Corporate Information Factory; The Data warehouse component; The external world component

    Introduction to Dimensional Modeling

    Multidimensional Model; Data warehouse requirements; Basic dimensional modeling techniques

    Advanced Dimensional Modeling

    Star and snowflake schemas; Extended dimension table designs; Extended fact table designs

    Building Dimensional Models

    Data warehouse management; Data warehouse bus architecture matrix; Managing the dimensional project

    Implementation of the data warehouse component

    Aggregation goals and risks; Aggregation development; Aggregation navigation

    Physical design, Indexing, Physical storage

    Standards; Indexing and Physical storage structure

    Data extraction, transformation and loading(ETL)

    Operational Data Store; Data Staging and ETL Strategies

    End User applications and Online analytical processing

    The application component; Decision support

    Data warehouse lifecycle and project management

    Development and maintenance process; The business dimensional lifecycle; Data warehouse project management and data warehouse processes

    Data warehouse architectures and back room functions

    Back room Functions and Architecture; Data storage; Managing the corporate information factory; Enterprise framework

    Infrastructure and Metadata

    Metadata repositories, security; Data warehouse infrastructure and environment security; Data warehouse metadata


    Bob Hendry