DBW624 Course Outline

Course Code: DBW624
Course Name: Introduction to Datawarehousing
Offered Date: Winter - 2022 | Other versions
Print Outline
Course Description:
The data warehousing marketplace continues to be one of the fastest growing areas of technology application. Whether it's used with CRM, ERP, e-Commerce, Financial Analysis, Sales Analysis or any of a large number of other disciplines, data warehousing has become an essential business tool for making informed decisions. This subject introduces students to data warehousing concepts. The subject uses a hands-on project to design and develop a data warehouse. Star schema fact tables and dimension tables will be examined. Multidimensional databases are emphasized as the students build on their database knowledge. A team project will be used to handle the process of moving data from an OLTP system to a DW with management reports through the cube and pivotal tables. Microsoft SQL server 2005 Analysis Services will be used to develop OLAP cubes and Microsoft Excel for OLAP reporting.
Credit Status: 1 credit in the CPA/CPAC Programs
Prerequisite: DBS311
Mode of Instruction: 2 hours interactive lecture per week.
2 hours lab time per week.
Learning Outcomes:
1. Explain the goals of data warehousing

2. Create OLAP reports from the data cube using Excel

3. Explain accepted Datawarehouse terminology

4. Identify the stages of the data warehousing lifecycle

5. Denormalize relational tables into high level summary tables

6. Apply the star schema model to a business case problem

7. Compare star schema and snowflake schema

8. Design and Implement a multidimensional data cube using SQL Server Analysis Services

9. Create OLAP-enabled web pages
Topic Outline:
  • Concepts - 15%
    •         Reasons for data warehousing
    •         Terminology
    •         Data warehousing compared to OLTP
    •         Components of a data warehouse
    •         The data warehouse lifecycle
    •         Managing the data warehouse
  • Data Warehouse Design - 30%
    •         Discussion of how DW database design differs from transactional database design
    •         Grain
    •         Facts and dimensions
    •         Star and snowflake schema
    •         Denormalize from OLTP, planned redundancy
    •         Data marts and conformed dimensions
    •         Strategies for maintaining the data warehouse
    •         Meta data in a DW
    •         Security in a DW
  • OLAP Cubes Design with SQL Server Analysis Services - 50%
    •         Analysis Services components and architecture
    •         Define dimensions with Dimension Editor
    •         Dimension levels and hierarchies
    •         Define cubes and measure with Cube Editor
    •         Process dimensions and cubes
    •         Cube storage design
    •         Create calculated members
    •         Virtual cubes
    •         Manage Partitions
    •         Implement drillthrough and cube writeback
    •         Cube security
    •         Roles of Data Transformation Services (DTS)
  • Data Mining - 5%
    •         Fundamental data mining terminology and concepts
    •         Use of built-in Analysis Manager wizards
Prescribed Text(s):
None
Reference Material:
Supply:
None
Promotion Policy:
To obtain a credit in this subject, a student must:
  •     Achieve a grade of 50% or better on the final exam
  •     Satisfactorily complete all assignments
  •     Achieve a weighted average of 50% or better for the tests and final exam
  •     Achieve a grade of 50% or better on the overall course


http://www.senecacollege.ca/about/policies/student-progression-and-promotion-policy.html

Grading Policyhttp://www.senecacollege.ca/about/policies/grading-policy.html

A+ 90%  to  100%
A 80%  to  89%
B+ 75%  to  79%
B 70%  to  74%
C+ 65%  to  69%
C 60%  to  64%
D+ 55%  to  59%
D 50%  to  54%
F 0%    to  49% (Not a Pass)
OR
EXC Excellent
SAT Satisfactory
UNSAT Unsatisfactory

For further information, see a copy of the Academic Policy, available online (http://www.senecacollege.ca/about/policies/academics-and-student-services.html) or at Seneca's Registrar's Offices. (https://www.senecacollege.ca/registrar.html).


Evaluation:

Tests (2) 30%
Assignment - Design 10%
Project - Team 30%
Final Exam 30%
Approved By:
Kathy Dumanski
Cheating and Plagiarism:
Seneca upholds a learning community that values academic integrity, honesty, fairness, trust, respect, responsibility and courage. These values enhance Seneca's commitment to deliver high-quality education and teaching excellence, while supporting a positive learning environment. Ensure that you are aware of Seneca's Academic Integrity Policy which can be found at: http://www.senecacollege.ca/about/policies/academic-integrity-policy.html Review section 2 of the policy for details regarding approaches to supporting integrity. Section 2.3 and Appendix B of the policy describe various sanctions that can be applied, if there is suspected academic misconduct (e.g., contract cheating, cheating, falsification, impersonation or plagiarism).

Please visit the Academic Integrity website http://open2.senecac.on.ca/sites/academic-integrity/for-students to understand and learn more about how to prepare and submit work so that it supports academic integrity, and to avoid academic misconduct.
Discrimination and Harassment:
All students and employees have the right to study and work in an environment that is free from discrimination and/or harassment. Language or activities that defeat this objective violate the College Policy on Discrimination/Harassment and shall not be tolerated. Information and assistance are available from the Student Conduct Office at student.conduct@senecacollege.ca.
Accomodation for Students with Disabilities
The College will provide reasonable accommodation to students with disabilities in order to promote academic success. If you require accommodation, contact the Counselling and Accessibility Services Office at ext. 22900 to initiate the process for documenting, assessing and implementing your individual accommodation needs.