Dr. Youry Khmelevsky
Data Warehousing Workshop I
Time & Date: 8:00–11:30 am, Friday, October 8, 2021
This workshop was developed for the Computer Science students with Database Systems Option or with a similar specialization (BCIS program at OC: https://www.okanagan.bc.ca/bachelor-of-computer-information-systems-degree). It can be especially a subject of interest for the students involved in industrial applied research. This workshop can be useful for anybody interested in Data Warehousing and current trends in the industry with a minimal background in DBMS systems, especially if you are going to build your own data warehouse at your company or for learning purposes. The following materials will be used during the workshop: The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling By: Ralph Kimball, Margy Ross (https://www.oreilly.com/library/view/the-data-warehouse/9781118530801/), Oracle® Database Data Warehousing Guide (https://docs.oracle.com/en/database/oracle/oracle-database/19/dwhsg/database-data-warehousing-guide.pdf) and some other additional sources.
Youry Khmelevsky received his Ph.D. degree in computer science and MSc in Electrical Engineering. His current research interests include software engineering; cloud and high-performance computing; enterprise-wide information systems; no programming paradigm, blind computing; and interdisciplinary applied computer science research. Dr. Khmelevsky had served as a postdoctoral fellow at Harvard University; was a Visiting Scientist in the Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT); was an Invited Researcher at Database Management and Machine Learning Department, Sorbonne University, Paris, France; held engineering and R&D positions in Industry in Europe and North America for about 15 years, including at Alberta Energy, Government of Alberta, Canada.
For further information please contact: Youry Khmelevsky (email: Youry at IEEE.org)
Registration is opened now: https://events.vtools.ieee.org/m/284762