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

    Prerequisites:
    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

    CEU:
    4.5

    Instructor:
    Bob Hendry