INFO634-23S2 (C) Semester Two 2023

Data Analytics & Business Intelligence

15 points

Details:
Start Date: Monday, 17 July 2023
End Date: Sunday, 12 November 2023
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 30 July 2023
  • Without academic penalty (including no fee refund): Sunday, 1 October 2023

Description

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, and exploratory data analysis, and apply these to decision-making in organisations.

Learning Outcomes

  • At the end of this course, students will be able to:
  • Demonstrate an understanding of key data science/analytics concepts, tools and techniques
  • To recognise and analyse business problems, issues and opportunities related to the role and use of data science/ analytics in organisations
  • 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.
  • Produce appropriate information models and reports for use in business decision-making using Data Science/ Analytics software/visualisation tools
  • Work as a team to perform key activities related to the analysis of data and business decisions and the 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.

Prerequisites

Subject to approval of the Head of Department

Course Coordinator

Pan Zheng

Lecturer

Annette Mills

Tutor

Susie Deng

Assessment

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

Indicative Fees

Domestic fee $1,051.00

* 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 .

All INFO634 Occurrences

  • INFO634-23S2 (C) Semester Two 2023
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