CQUniversity Unit Profile

In Progress

Please note that this Unit Profile is still in progress. The content below is subject to change.
COIT20253 Business Intelligence using Big Data
Business Intelligence using Big Data
Save or Print as PDF
All details in this unit profile for COIT20253 have been officially approved by CQUniversity and represent a learning partnership between the University and you (our student).
The information will not be changed unless absolutely necessary and any change will be clearly indicated by an approved correction included in the profile.
General Information

Overview

Big data is a popular term used to describe the exponential growth and availability of structured and unstructured data and business intelligence involves collecting, processing, analysing, and visualising data to help organisations make informed business decisions. In this unit, you will learn concepts of business intelligence, the alignment of big data with business intelligence, and how big data technologies can be leveraged to build organisational business intelligence. You will also explore contemporary tools in business intelligence and gain an understanding of data ethics, ensuring that data-driven solutions are developed and implemented responsibly and transparently. You will learn how to use big data for decision-making and impacting change in organisations. To understand these, you will be introduced to big data analytical tools and technologies to help solve authentic business problems and make effective business decisions. This unit provides a comprehensive foundation in big data and business intelligence with a strong business focus, equipping you with the skills needed for a successful career in data analytics along with expertise in big data strategy, architecture, and data ethics.

Details

Career Level: Postgraduate
Unit Level: Level 9
Credit Points: 6
Student Contribution Band: 8
Fraction of Full-Time Student Load: 0.125

Pre-requisites or Co-requisites

Prerequisites: COIT20250 Technologies in Information Systems Practice, and COIT20245 Introduction to Programming, and COIT20247 Database Design and Development. Anti-Requisites: COIT20236 Business Intelligence Management 

Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework).

Offerings For Term 1 - 2025

Brisbane
Melbourne
Online
Sydney

Attendance Requirements

All on-campus students are expected to attend scheduled classes - in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).

Website

This unit has a website, within the Moodle system, which is available two weeks before the start of term. It is important that you visit your Moodle site throughout the term. Please visit Moodle for more information.

Class and Assessment Overview

Information for Class and Assessment Overview has not been released yet.

This information will be available on Monday 13 January 2025
CQUniversity Policies

All University policies are available on the CQUniversity Policy site.

You may wish to view these policies:


This list is not an exhaustive list of all University policies. The full list of University policies are available on the CQUniversity Policy site.

Previous Student Feedback

Feedback, Recommendations and Responses

Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.

Feedback from Student Unit and Teaching Evaluation

Feedback

Most students rated the unit as Exceptional.

Recommendation

To continue with the good practices.

Feedback from ICT Course Committee

Feedback

Aligning the unit with the latest SFIA 9 released.

Recommendation

To identify and integrate specific SFIA 9 skill categories relevant to the unit.

Feedback from Classroom Feedback

Feedback

More hands-on exercises.

Recommendation

To add tutorial exercises based on the Spark ecosystem running in Google Colab, by referencing resources such as https://praxis-qr.github.io/BDSN/ ;https://colab.research.google.com/github/pnavaro/big-data/.

Unit Learning Outcomes

Information for Unit Learning Outcomes has not been released yet.

This information will be available on Monday 13 January 2025
Alignment of Learning Outcomes, Assessment and Graduate Attributes

Information for Alignment of Learning Outcomes, Assessment and Graduate Attributes has not been released yet.

This information will be available on Monday 13 January 2025
Textbooks and Resources

Information for Textbooks and Resources has not been released yet.

This information will be available on Monday 17 February 2025
Academic Integrity Statement

Information for Academic Integrity Statement has not been released yet.

This unit profile has not yet been finalised.