Business Data Analytics
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"ICMS' Work Integrated Learning gave me the ability to gain real life experience before I even graduated".
Alana Williams
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Bachelor of Business (Marketing)
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Bachelor of Business (Sports Management)
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This subject is available under ICMS undergraduate degrees, please click the button below to find an undergraduate course for you.
Subject Code:
DAT102A
Subject Type:
Specialisation
Credit Points:
3 credit points
Pre-requisite/Co-requisite:
None
Subject Level:
100
Subject Rationale:
Business data analytics offers students a set of powerful tools to collect, transform, analyse and report data enabling organisations to make more informed strategic decisions. The subject is designed to equip students with the relevant business analytics techniques and tools to define, analyse, solve and communicate business problems. Students will learn how to gather business requirements and how to collect and transform internal and external data for further analyses. The challenges of building a robust data model based on business requirements and available data will be covered.
Students will explore contemporary analysis techniques to identify patterns in structured and unstructured data and to derive actionable insights that help decision-makers to solve a variety of business problems. They will also learn about the statistical concepts that underpin the different types of analysis such as measures of central tendency, dispersion and position, sampling, and hypothesis development and testing. Students will also be introduced to the foundations of effective communication and visualisation techniques.
Learning Outcomes:
a) Describe key data analytics concepts, tools and methodologies.
b) Evaluate business requirements and translate them into analytical use cases
c) Evaluate and prepare data for further analysis.
d) Apply a range of data analysis techniques to solve specific business problems, in line with ethical, regulatory and compliance requirements.
e) Interpret, effectively visualise and communicate the results of data analyses to key stakeholders.
Student Assessment:
| No | Assessment Task | Weighting | Learning Outcomes |
| 1 | Skills Application/ Practical | 10% | a,b,c,d |
| 10% | |||
| 2 | Business Analysis Report | 35% | a,b,c,d,e |
| 3 | Data Analytics Project (G) | ||
| Part A Business Report | 30% | b,c,d,e | |
| Part B Presentation | 15% |
Broad Topics to be Covered:
W1: Introduction to business data analytics
|
W2: Developing organisational business data analytics capabilities
|
W3: Data exploration with descriptive statistics
|
W4: Applied diagnostic analytics
|
W5: Exploring relationships with inferential statistics
|
W6: Applied predictive analytics
|
W7: Applied prescriptive analytics
|
W8: Text, web, and social media analytics
|
W9: Effective data visualisation
|
W10: Effective data storytelling and presentation
|
W11: Ethics in data science and future trends in business data analytics
|
Please note that these topics are often refined and subject to change so for up to date weekly topics and suggested reading resources, please refer to the Moodle subject page.