Database II

Curriculum guideline

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Course
CSIS 3300
Discontinued
No
Course code
CSIS 3300
Descriptive
Database II
Department
Computing Studies & Information Systems
Faculty
Commerce & Business Administration
Credits
3.00
Start date
End term
Not Specified
PLAR
No
Semester length
15 Weeks
Max class size
35
Contact hours
Lecture: 2 Hours per week Seminar: 2 Hours per week Total: 4 Hours per week
Method(s) of instruction
Lecture
Seminar
Learning activities

Lecture, seminar and hands-on exercises in the lab.

Course description
This course will continue on from CSIS 2300 exploring advanced features of database systems. Topics covered will include indexing; query processing and optimization; transaction processing; denormalization; star schema; DW/OLAP cubes; security. NoSQL and MapReduce will also be covered.
Course content
  1. Course overview and review of database fundamentals;
  2. Working with DB indexes;
  3. Introduction to query processing and optimization;
  4. Query optimization case studies;
  5. Working with DB transactions;
  6. Denormalizing a DB - why, when, and how;
  7. Introduction to dimensional modeling;
  8. Designing a star schema;
  9. Working with DW/OLAP cube;
  10. Introduction to noSQL databases;
  11. CRUD operations in noSQL;
  12. Analytics in noSQL (MapReduce);
  13. Securing a database system.
Learning outcomes

At the end of this course, the successful student will be able to:

  1. Explain the purpose of indexing;
  2. List different types of indexes;
  3. Evaluate and explain when to use an index on a column;
  4. Describe how a SQL query is processed by the DB engine;
  5. Generate a more efficient query which reduces resource consumption but provides same data results;
  6. Explain situations when DB transactions should be used;
  7. Plan a set of queries which could be executed as part of a transaction - including both the success and failure scenarios;
  8. Describe why and when denormalization is beneficial for a DB system;
  9. Execute the denormalization process;
  10. Design a star schema;
  11. Use a DW/OLAP cube to extract information from data;
  12. Use a noSQL DB to perform CRUD (Create, Retrieve, Update, Delete) operations;
  13. Demonstrate application of MapReduce functions;
  14. Describe common DB security issues and their solutions.
Means of assessment
   
Assignments/Project:    10% - 25%
Quizzes (Minimum 2) 10% - 20%
Midterm exam  20% - 30%
Final Exam * 30% - 40%
Total 100%

Some of the assessments may involve group work.

* Practical hands-on computer exam

In order to pass the course, students must, in addition to receiving an overall course grade of 50%, also achieve a grade of at least 50% on the combined weighted examination components (including quizzes, tests, exams).

Students may conduct research as part of their coursework in this class. Instructors for the course are responsible for ensuring that student research projects comply with College policies on ethical conduct for research involving humans, which can require obtaining Informed Consent from participants and getting the approval of the Douglas College Research Ethics Board prior to conducting the research.

Textbook materials

Instructor compiled materials

and/or

other textbooks as approved by the department

Prerequisites

Min grade C in CSIS 2300 

Equivalencies

Courses listed here are equivalent to this course and cannot be taken for further credit:

  • No equivalency courses