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.
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

