Students will study, discuss, and compare current processes and tools being used by organizations for their data-handling needs.

Topics include performance issues, hands-on database administration, an introduction to data warehousing and data mining, and machine learning on top of the data warehouses.

Learning Outcomes

Upon successful completion of this course, students will be able to:

• Explain how optimization techniques enable RDBMS to perform better.

• Identify issues involved in tuning and measuring RDBMS performance.

• Explain how object-oriented (OODBMS) and object-relational (ORDBMS) databases differ from relational, and when each is useful and preferable.

• Describe what data warehousing is and the fundamental issues that affect its construction and performance.

• Explain what data mining is and the methods used.

• Execute database administrator responsibilities and duties.

• Use data warehouses and describe how each specific topic in the course is useful in solving business problems.

Resources

Course Content

• Relational optimization techniques.

• Performance tuning.

• Comparison of modern relational systems.

• Data warehousing and data mining.

• Oracle’s current architecture.

• Oracle’s current database administration.

Textbooks & Materials

–   Data Mining: Concepts and Techniques Paperback – Oct. 3 2022, by Jiawei Han (Author), Jian Pei (Author), Hanghang Tong (Author) (Amazon: https://www.amazon.ca/Data-Mining-Techniques-Jiawei-Han-dp-0128117605/dp/0128117605/ref=dp_ob_image_bk)

–   Data Mining: Concepts and Techniques, 3rd ed., The Morgan Kaufmann Series in Data Management Systems, Morgan Kaufmann Publishers, July 2011. ISBN 978-0123814791

•       https://hanj.cs.illinois.edu/bk3/

–   Connolly & Begg Database Systems, 2010 Oracle Education Kit – Oracle 11 g DBA Fundamentals Addison-Wesley 2010

–   The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modelling (Edition: 3rd) By: Ralph Kimball, Margy Ross. Publisher: John Wiley & Sons P&T. Print ISBN: 9781118530801, 1118530802, eText ISBN: 9781118530771, 1118530772

•       Amazon: https://www.amazon.ca/Data-Warehouse-Toolkit-Definitive-Dimensional/dp/1118530802

•       O’Reilly: https://learning.oreilly.com/library/view/the-data-warehouse/9781118530801/

–      Supplementary Resources: 

–      Deep Learning with Python by Francois Chollet. Publisher: Manning Publications, December 2017, ISBN: 9781617294433. 

–      Visualization Analysis and Design by Tamara Munzner, Publisher: A K Peters/CRC Press, December 2014.

–      Information Visualization, 3rd Edition by Colin Ware, Publisher: Morgan Kaufmann, May 2012, ISBN: 9780123814654

–      Introduction to Data Mining by Pang-Ning Tan; Michael Steinbach; Anuj Karpatne; Vipin Kumar, Edition: 2nd2019, Publisher: Pearson.

–      Data Warehousing Fundamentals for IT Professionals (Edition: 2nd, 2010) By Paulraj Ponniah Publisher: Wiley-Blackwell. Print ISBN: 9780470462072, 0470462078, eText ISBN: 9781119108528, 1119108527 

–      The Data Warehouse Lifecycle Toolkit “Expert methods for designing, developing, and deploying Data Warehouses, Ralph Kimball, Laura Reeves, Margy Ross, Warren Thornthwaite, ISBN 0-471-25547-5.

–      Oracle Database 26ai Data Warehousing https://docs.oracle.com/en/database/oracle/oracle-database/26/dwhsg/index.html 

–      Data Camp: https://www.datacamp.com

–      Oracle Academy: https://myacademy.oracle.com

  –     https://www.oracle.com/security/ & https://www.oracle.com/security/database-security/ 

2024Less07_Users.ppt 

2024Less11_Security.ppt

  Less13_Performance.ppt

  –    https://www.oracle.com/database/free/ 

  –     https://www.ateam-oracle.com/oci-tenancy-security-best-practices-guide-overview 

https://docs.google.com/presentation/d/1OrNCKArOyZWOwPKClmndnqJDuqxL8qEj/edit?usp=drive_link&ouid=105173229812140416561&rtpof=true&sd=true