ACCY6105 – Data Analytics
Module code
ACCY6105
Module title
Data Analytics
Prescription
The aim of this course is to develop the knowledge, skills, and competencies to analyse and evaluate business data to support decision-making.
Programmes
- BI1401
- TP4775
NZQA Level
Level 6
NZQA Credits
15
Delivery method
- Web-Supported
Learning hours
- Total learning hours
- 150
Resources required
- Learning Outcomes
- 1. Examine the role of data analytics in a business context.
2. Analyse requirements and implement queries.
3. Apply statistical tools and techniques to inform appropriate solutions to business problems.
4. Discuss the ethical implications associated with data utilisation. - Content
- LO1
• Basics of business analytics: thinking analytically and introduction to terminology
• Classical statistics vs business analytics
• Producer of useful information
LO2
• Data mining methodology and data warehouse extractions
• Querying large-scale databases
• Data distribution, data warehouses
• Data preparation and cleaning
• Non-parametric tests
• Data visualisation
• Data modelling and evaluation
LO3
• Decision Making Theory
• Business Intelligence
• Using predictive modelling
• Decision making and analytic tools e.g., Web Intelligence or Excel, Tableau or PowerBi
• Design of decision-making experiments
• Data visualisation
• Forecasting concepts using linear and logistic regression, measures of distance, scaling and ordination
LO4
• Ethical and privacy implications, including ethics of big data
• Role of a responsible custodian of data - Teaching and Learning Strategy
- All learning and teaching activities as described in the approved programme and delivery documents are enabled for this course unless specified.
- Basic of Assessment
- Assessment in this course employs an achievement-based grading scheme. Learners will be advised of all matters relating to summative assessment prior to the start of the course.
- Assessment Criteria
- The portfolio is comprised of multiple components. Learners need to provide sufficient evidence against all learning outcomes and gain an overall mark of at least 50% in order to pass this module.
(A minimum of 50% of the portfolio assessment activities will be controlled (supervised/observed) - Learning and Teaching Resource
- All required and recommended resource are provided to learners via course outlines.
