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.
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.
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.
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