INFO361-22S2 (C) Semester Two 2022

Business Intelligence and Analytics

15 points

Details:
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

Description

This course covers key principles and practices related to the use of business intelligence (BI) systems to support strategy and decision-making. Topics include performance dashboards and data visualisation; descriptive, predictive and predictive analytics; data, text and web mining; future trends and directions. Real data-sets and industry-standard tools will be used to demonstrate key principles of BI and to help students develop analytical and problem-solving skills related to BI solutions.

Business Intelligence (BI) Systems use various technologies, processes and applications to analyse operational, social and other data (e.g. structured and unstructured, internal and external data) and identify patterns, trends and relationships that can be used to support an organisation’s business objectives and managerial decision making. The term ‘business intelligence’ describes both the product and the process by which organisations obtain, analyse and distribute ‘business intelligence’. The course tackles business intelligence and analytics from both practical and theoretical aspects. Students will be exposed to relevant concepts and approaches of BI and BA and gain experience in developing data-driven solutions to practical business problems.

Students completing this course will have a thorough understanding of BA and BI related subject matters, and develop skills in processing and interpreting business data independently for practical solutions, including data understanding, data handling, data visualisation, trend prediction, regression model, simple machine learning and apply these to decision-making.

Learning Outcomes

  • At the end of this course, it is expected that students will have gained an understanding of key BI concepts, and practical approaches to dealing with data-driven business problems. Specifically, it is expected that students will be able to:
  • Demonstrate an understanding of key business analytics concepts, tools and techniques.
  • Recognise and analyse business problems, issues and opportunities related to the role and use of business data in organisations.
  • Select and apply suitable techniques (e.g. prediction and classification), extract meaningful insights from various data, and make recommendations that align with the organisation’s context/objectives and business decisions.
  • Produce appropriate information models and reports for business decision-making using relevant
    programming and visualisation tools
  • 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.

      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.

      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) INFO123; and (2) 45 points at 200-level or above RP: STAT101

Recommended Preparation

Timetable 2022

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Tuesday 10:00 - 12:00 Jack Erskine 001 Computer Lab
18 Jul - 28 Aug
12 Sep - 23 Oct
Lab A
Activity Day Time Location Weeks
01 Friday 10:00 - 11:00 Ernest Rutherford 464 Computer Lab
18 Jul - 28 Aug
12 Sep - 23 Oct

Course Coordinator

Pan Zheng

Lecturer

Claris Chung

Tutor

Thilini Bhagya

Assessment

Assessment Due Date Percentage 
Individual Lab Tasks (x3) 15%
Group Project 30%
Mid-term test 15%
Final Exam 40%

Textbooks / Resources

Lecture slides, example codes, handouts, article links, research articles and reading materials shared on LEARN.

Course links

Learn

Indicative Fees

Domestic fee $892.00

International fee $4,563.00

* 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 INFO361 Occurrences

  • INFO361-22S2 (C) Semester Two 2022