INFO634-22S2 (C) Semester Two 2022

Data Analytics & Business Intelligence

15 points

Start Date: Monday, 18 July 2022
End Date: Sunday, 13 November 2022
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 31 July 2022
  • Without academic penalty (including no fee refund): Sunday, 2 October 2022


The aim is to help students develop an understanding and gain experience with key aspects of business data analytics its applications, systems, processes and practices, and be able to engage critically with the opportunities, issues and challenges that underpin supporting and engaging with business intelligence and analytics in organisations. Key concepts, analytical techniques and tools applicable to various aspects of data science/business analytics, including the collection, integration, analysis, and presentation of organisational information, and data-driven decision making in businesses and otherwise are introduced and applied.

The aim of this course is to help students develop an understanding of data science/
analytics, and provide an opportunity to gain experience with diverse methods and
technologies related to common aspects of data science/analytics. Key concepts,
analytical techniques and tools applicable to different aspects of data science/analytics
and business decision making (i.e. business intelligence (BI)) are introduced.

Students completing this course have an opportunity to develop foundational skills in the
use of common data science/analytics tools, including data handling, data visualisation,
regression, neural networks, decision trees, time series analysis,

Learning Outcomes

At the end of this course, students will be able to:
1. Demonstrate an understanding of key data science/analytics concepts, tools and techniques
2. To recognise and analyse business problems, issues and opportunities related to the role
and use of data science/ analytics in organisations
3. To select and apply suitable techniques (e.g. forecasting, data mining), extract meaningful insights from various data, and make recommendations that align with the organisations’ context/objectives and business decisions.
4. Produce appropriate information models and reports for use in business decision-making using Data Science/ Analytics software/visualisation tools
5. Work as a team to perform key activities related to the analysis of data and business decisions and provision of meaningful insights (BI) and evidence-based recommendations.

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.

Engaged with the community

Students will have observed and understood a culture within a community by reflecting on their own performance and experiences within that community.


Subject to approval of the Head of Department

Timetable 2022

Students must attend one activity from each section.

Computer Lab A
Activity Day Time Location Weeks
01 Friday 15:00 - 18:00 Ernest Rutherford 464 Computer Lab
18 Jul - 28 Aug
12 Sep - 23 Oct

Course Coordinator

Pan Zheng


Annette Mills


Assessment Due Date Percentage 
Assignments 10%
Individual Essay 20%
Project 30%
Final Test 40%

Indicative Fees

Domestic fee $1,023.00

* 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 5 people apply to enrol.

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

All INFO634 Occurrences

  • INFO634-22S2 (C) Semester Two 2022