INFO260-26S2 (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

The course introduces a range of topics that underpin data management in contemporary organisations. The first part of the course focuses on data architecture, data modelling, data administration, and data warehousing. The second part of the course introduces the concepts of Big Data. In its wider scope the course is designed to expose the students to real-life issues in data management and database management systems in the modern environment.

INFO260 introduces the principles and practices of enterprise data management, treating data as a strategic organisational asset. Students explore the complete data management lifecycle, including data governance, modelling, database design, data quality, metadata, master and reference data, integration, data warehousing, and business intelligence. The course examines how effective data management enables trustworthy analytics, organisational decision making, regulatory compliance, and digital transformation. Contemporary topics such as Big Data, cloud-based data platforms, ethical data management, and responsible AI are introduced to prepare students for further study and professional practice in analytics, information systems, and AI-enabled organisations.

Learning Outcomes

The objectives of the course are:
1. Explain and apply the principles of enterprise data management to support trustworthy organisational data and decision making.
2. Design and implement data models and relational databases using industry-standard methods and tools.
3. Evaluate enterprise data management practices, including governance, quality, metadata, integration, master data, and data warehousing, in organisational contexts.
4. Analyse ethical, cultural, and professional responsibilities in data management, including Te Tiriti-informed approaches, Māori Data Sovereignty, and responsible AI.
5. Critically evaluate contemporary data management challenges and opportunities associated with Big Data, Business Intelligence, cloud computing, and artificial intelligence.

University Graduate Attributes

This course will provide students with an opportunity to develop the Graduate Attributes specified below:

Critically competent in a core academic discipline of their award

Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.

Employable, innovative and enterprising

Students will develop key skills and attributes sought by employers that can be used in a range of applications.

Biculturally competent and confident

Students will be aware of and understand the nature of biculturalism in Aotearoa New Zealand, and its relevance to their area of study and/or their degree.

Prerequisites

1) INFO123 or INFO125 or COSC101 or COSC121 or COSC131 or COSC122 or DIGI101; and (2) An additional 15 points

Timetable 2026

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Monday 12:00 - 14:00 F3 Lecture Theatre
13 Jul - 23 Aug
7 Sep - 18 Oct
Computer Lab A
Activity Day Time Location Weeks
01 Wednesday 14:00 - 15:00 Ernest Rutherford 212 Computer Lab
13 Jul - 23 Aug
7 Sep - 18 Oct
02 Wednesday 16:00 - 17:00 Rehua 008 Computer Lab
13 Jul - 23 Aug
7 Sep - 18 Oct
03 Wednesday 17:00 - 18:00 Rehua 008 Computer Lab
13 Jul - 23 Aug
7 Sep - 18 Oct
04 Thursday 13:00 - 14:00 Ernest Rutherford 212 Computer Lab
13 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 Otakaro 236 L2 Lecture Theatre
17 Aug - 23 Aug

Course Coordinator / Lecturer

Claris Chung

Assessment

Assessment Due Date Percentage 
Course Project 30%
Mid-semester test 30%
Final Exam 40%

Course links

Learn

Indicative Fees

Domestic fee $1,058.00

International fee $5,388.00

* 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.

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

All INFO260 Occurrences

  • INFO260-26S2 (C) Semester Two 2026