INFO261-26S1 (C) Semester One 2026

Introduction to Business Analytics

15 points

Details:
Start Date: Monday, 16 February 2026
End Date: Sunday, 21 June 2026
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 1 March 2026
  • Without academic penalty (including no fee refund): Sunday, 10 May 2026

Description

Business analytics is a field that studies, interprets and visualises data to uncover patterns and insights that support informed decision-making. It produces actionable knowledge that can suggest how to improve business outcomes. This course introduces fundamental data analytics approaches and technology platforms widely used in industry practice. It addresses problems and opportunities comprehensively in order to translate business problems, specify questions, prepare, analyse, visualise data and recommend actions. Students apply tools and techniques to various business contexts such as marketing, accounting, finance and operations management.

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

Students completing this course have an opportunity to develop fundamental skills in the use of common business analytics tools including data visualisation/visual analytics, regression, cluster analysis and exploratory data analysis, and apply these to decision-making in organisations.

Learning Outcomes

The objectives of the course are:
1) Demonstrate an understanding of key business data analytics concepts, tools and techniques.
2) To recognise and demonstrate an understanding of issues related to the use of business data for decision-making including data ownership and ethical considerations.
3) To recognise and analyse organisational problems and opportunities related to the role and use of data analytics in organisations.
4) To select and apply suitable techniques (e.g. regression, forecasting, cluster analysis, visualisation), extract meaningful insights from various data and make recommendations that align with the organisations’ context and objectives.
5) To perform key activities related to the analysis of organisational data and provide and communicate 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.

Globally aware

Students will comprehend the influence of global conditions on their discipline and will be competent in engaging with global and multi-cultural contexts.

Prerequisites

(1) 15 points from STAT101, DATA101, DIGI103; and (2) 15 points from INFO123, INFO125, COSC101, COSC121, COSC122, COSC131, DIGI101

Restrictions

Timetable 2026

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Tuesday 12:00 - 14:00 A2 Lecture Theatre
16 Feb - 29 Mar
20 Apr - 31 May
Computer Lab A
Activity Day Time Location Weeks
01 Thursday 12:00 - 13:00 Ernest Rutherford 212 Computer Lab
23 Feb - 29 Mar
20 Apr - 31 May
02 Thursday 17:00 - 18:00 Ernest Rutherford 212 Computer Lab
23 Feb - 29 Mar
20 Apr - 31 May
03 Friday 13:00 - 14:00 Rehua 008 Computer Lab
23 Feb - 29 Mar
20 Apr - 31 May
04 Thursday 09:00 - 10:00 Jack Erskine 248 Computer Lab
23 Feb - 29 Mar
20 Apr - 31 May
05 Thursday 11:00 - 12:00 Rehua 008 Computer Lab
23 Feb - 29 Mar
20 Apr - 31 May

Examinations, Quizzes and Formal Tests

Test A
Activity Day Time Location Weeks
01 Monday 19:00 - 21:00 K1 Lecture Theatre
20 Apr - 26 Apr

Course Coordinator

Nelly Todorova

Assessment

Assessment Due Date Percentage 
Lab Assignments 20%
Tutorial Submissions 8%
Term Test 30%
Final Exam 42%

Textbooks / Resources

Required Texts

Vernon J. Richardson | Marcia Watson; Introduction to Business Analytics ; McGraw Hill LLC, 2024.

Reference Text:  Storytelling with Data: Let's Practice! by Cole N. Knaflic 2020

Software:  Excel, Power BI, Tableau Desktop (Education Licences will be provided by the course, check LEARN for details)

Indicative Fees

Domestic fee $1,038.00

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 INFO261 Occurrences

  • INFO261-26S1 (C) Semester One 2026