MBIS623-26S2 (C) Semester Two 2026

Data Management

15 points

Details:
Start Date: Monday, 13 July 2026
End Date: Sunday, 8 November 2026
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 26 July 2026
  • Without academic penalty (including no fee refund): Sunday, 27 September 2026

Description

This course covers the principles and practices that underpin the effective use and management of data in modern organizations. It includes core topics such as data governance, data modelling, data quality, data integration, data sovereignty, SQL querying, and principles of data security, ethics and privacy. The course exposes the students to real-world challenges and considerations in managing and using data to support business decision-making. Emphasis is placed on practical skills and real-world applications.

MBIS623 introduces a range of topics that underpin the successful use and management of information in contemporary organisations. MBIS623 focuses on data governance, data modelling, data storage and operations, data administration, data quality, data security and data warehousing. The course introduces the concepts of Big Data which drive many modern decision-making processes. Big Data platforms and cloudbased analytics bring significant cost advantages, when it comes to processing large amounts of data with a view to identify more efficient ways of doing business.  
The topics included in MBIS623 are a part of the Australian Computer Society (ACS) and Institute of IT Professionals New Zealand (IIT PNZ) Core Body of Knowledge and the Model Curriculum and Guidelines for Information Systems at both the graduate and undergraduate levels. The material of the course draws on the Data Management Essentials certificate material developed by the British Computing Society (BCS) Chartered Institute of IT, as well as the material included in the Data Management International (DAMA) body of knowledge.

Learning Outcomes

The outcomes of the course are:
1. Demonstrate knowledge of the goals, principles and functions of data management.
2. Design a data model using a standard industrial data modelling tool/notation.
3. Implement a database using a standard industrial data management tool.
4. Demonstrate the understanding and skills required for data administration and repository
administration.
5. Analyse the roles that information systems professionals perform in data management.
6. Evaluate data management processes and practices in contemporary organisations.

Restrictions

Timetable 2026

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Friday 09:00 - 12:00 E5 Lecture Theatre
13 Jul - 23 Aug
7 Sep - 18 Oct
Computer Lab A
Activity Day Time Location Weeks
01 Wednesday 11:00 - 12:00 Jack Erskine 001 Computer Lab
20 Jul - 23 Aug
7 Sep - 18 Oct
02 Thursday 12:00 - 13:00 Ernest Rutherford 212 Computer Lab
20 Jul - 23 Aug
7 Sep - 18 Oct
03 Thursday 11:00 - 12:00 Ernest Rutherford 212 Computer Lab
20 Jul - 23 Aug
7 Sep - 18 Oct

Examinations, Quizzes and Formal Tests

Test A
Activity Day Time Location Weeks
01 Tuesday 18:30 - 20:30 C3 Lecture Theatre
7 Sep - 13 Sep

Timetable Note

Friday 9:00–12:00pm – E5 Lecture Theatre
Lectures for this course are recorded using the ECHO360 lecture recording system.

Course Coordinator

Richard Derham

Assessment

Assessment Due Date Percentage 
Assignment 1: Data Modelling 15%
Assignment 2: Database Design 15%
Quizzes (best 3 of 4) 15%
Final Exam 30%
Term Test 25%


To pass this course you must not only achieve a final grade of 50% or higher, but also achieve a weighted average grade of at least 45% across all invigilated assessments.


Students with Disabilities

For information about examination support services, please refer to the University’s Equity & Disability Service: https://www.canterbury.ac.nz/equity-disability/


Special Considerations

UC has a process which allows students to apply for Special Consideration for poor performance in an assessment or a missed assessment due to unforeseen circumstances at the time of the assessment.  Special Consideration is not an extension. If you want an extension for an assignment or essay, contact your Course Coordinator.


Guidelines for the Use of AI in Coursework

The use of AI may or may not be permitted in courses. Within a course, permission may vary by assignment. It is the responsibility of the student to inform themselves about assessment conditions and submit work that is their own and that properly acknowledges the work of other people and tools, including generative artificial intelligence tools.
It is important to familiarise yourself with the UC Misconduct Procedure Guide for Students. Examples of academic misconduct include, but are not limited to:
Where a student uses a generative artificial intelligence (AI) tool for an assessment in a manner that is not expressly permitted or fails to acknowledge the use of a generative AI tool as instructed.


Assessment in Te Reo Māori

In recognising that Te Reo Māori is an official language of New Zealand, the University provides for students who may wish to use Te Reo Māori in their assessment. If you intend to submit your work in Te Reo Māori you are required to do the following:  
Read the Assessment in Te Reo Māori Policy and ensure that you meet the conditions set out in the policy. This includes, but is not limited to, informing the Course Coordinator 1) no later than 10 working days after the commencement of the course that you wish to use Te Reo Māori and 2) at least 15 working days before each assessment due date that you wish to use Te Reo Māori.

Textbooks / Resources

A large portion of the course reading material is available via the UC Library in hard copy and electronic formats. The MBIS623 UC LEARN site will be used to deliver lecture and tutorial material in electronic format.
The recommended readings for MBIS623 are as follows:  
1. Watson, R (2024), Data Management: Databases and Analytics, Open Edition.  
2. Hoffer, Jeffrey A., Ramesh, V., Topi, Heikki; (2019) Modern Database Management; Thirteenth Ed.  
3. Gordon, K. (2022). Principles of Data Management: Facilitating Information Sharing (3rd ed.). BCS Learning & Development Limited.
4.Earley, S., Henderson, D., Data Management Association. (2017). The Data Management Body of
Knowledge (2nd ed.). Technics Publications.

Indicative Fees

Domestic fee $1,198.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

Minimum enrolments

This course will not be offered if fewer than 10 people apply to enrol.

For further information see Department of Accounting and Information Systems on the departments and faculties page .

All MBIS623 Occurrences