As the use of big data become increasingly important to businesses, it is essential to analyse the data and provide meaningful view and knowledge to support judgment and action plans. This unit (NIT3171) provides students with advanced analytical methodologies and data mining models for ICT business analytics, as well as contemporary techniques to visualise the data for decision support. The content includes data preparation, association rule analysis, classification, clustering, regression, anomaly detection, building analytic models using SQL and data visualisation.
Unit details
Location:
Study level:
Undergraduate
Credit points:
12
Unit code:
NIT3171
Prerequisites
NIT2202 - Big Data or
BAO2001 - Corporate Finance and
NIT2171 - Introduction to ICT Management or
NIT2271 - ICT Change Management
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Learning Outcomes
| 1. | Critically review in a group (team work) the current algorithms, methodologies and modelling for ICT business analytics; | ||
| 2. | Evaluate in a group (team work) the various ICT business analytic tools and techniques; | ||
| 3. | Review in more depth the current algorithms, methodologies and modelling for ICT business analytics based on the outcome of the student group assignment deliverable; | ||
| 4. | Tabulate various ICT business analytic tools and techniques for the business interesting points finding from the student group work deliverable; and | ||
| 5. | Propose a business analytics report to solve practical problems identified in an ICT business project. |
Assessment
| Assessment type | Description | Grade |
|---|---|---|
| Test | 2 x Open book tests (Test 1 - 15%, Test 2 - 25%) | 40% |
| Project | Group Project on BA solution development | 30% |
| Assignment | Case Study Individual Report (15%) (Session 9) Individual Presentation (15%) (Session 10) | 30% |
Where to next?
As part of a course
This unit is studied as part of the following courses. Refer to the course page for information on how to apply for the course.
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