This course teaches the design and development of data warehouses. The OLTP and OLAP needs of businesses are analyzed to rationalize the need of data warehouses and corresponding data models. Data warehouse architectures ranging from ROLAP to MOLAP are developed and evaluated. Data models conducive to such needs are studied. Tools to develop in-house data warehouses are identified and practiced along with off-the-shelf data warehouse solutions including cloud based services. Role of competing concepts such as data lakes and big data is evaluated in the context of data warehousing.
Hybrid delivery format. This course will be a combination of in-class sessions (15 hours) AND online instruction (30 hours). Classroom sessions will be held on the following Tuesdays at the Downtown campus: January 7, February 4, and March 3. The final exam will be held on Tuesday, March 24 at the Downtown campus. All sessions will be from 18:30-22:15. ***This is not a self-paced course. There will be specific timelines for assignments and exams.*** Course content, kind and quality of assignments and general standards for this course are the same as classroom courses. You must have an email address and access to a computer capable of downloading basic documents.
A portion of seats are temporarily held for domestic students.
International students: this may impact your ability to register.
This section is only available for registration starting Wed, Oct 23 at 9:00 am (PDT)
Upon successful completion, the student will be able to:
Analyze OLTP and OLAP business needs and use traditional database systems vs data warehouses accordingly.
Design and implement ROLAP data models such as star and snow-flake to address OLAP business needs.
Design and implement MOLAP data models such as multidimensional cubes using off-the-shelf data warehousing solutions.
Design and implement ETL (extraction, transformation and loading) using tools such as stored procedures and triggers, database APIs and web services APIs to support data warehouse development needs.
Apply well-known data warehouse design and development process to implement data warehouses for real-world business intelligence needs.
Implement data warehouses utilizing enterprise as well as cloud based data warehouse solutions.
Design OLAP queries using SQL extensions and MDX.
Integrate off-the-shelf reporting and plotting tools with the data warehouse to evaluate its efficacy in supporting business intelligence.
Optimize scalability of data warehouse solutions.
Effective as of Fall 2019
COMP 8071 is offered as a part of the following programs:
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