In this module students will learn about business intelligence (BI) concepts, methods, and processes for decision support and business process improvement. The student will gain an in-depth theoretical understanding of organisation memory, information integration, insight creation, information presentation and business performance management methods.
This module aims to equip students with a comprehensive theoretical and practical appreciation of best practices in Business Intelligence. We make extensive use of a Business Intelligence application in lab sessions. You will learn how business intelligence assists companies in making good business decisions. Business Intelligence has capabilities of producing accurate visualisation reports by extracting data from organisation memory and integrating with big data. Other example technologies include analytical processing, analytics, data mining and business performance management. In lab exercises you will learn how to connect with data sources, gain insights through analytics and create visually appealing dashboards.
SETU Waterford is a member institution of Tableau Academic Program and Qlik Academic Program. Both academic programs provide curriculum material and licensed software.
Indicative Content:
Conceptual foundations of BI
Organisation memory – relevant technologies for developing and managing structured data
Accessing, cleansing and integrating different types of data
Information integration – integration of information from text, web mining and Big Data
Insight creation - data mining – methods and techniques
Information presentation – visual analytics, enterprise reporting and business performance management methods
Major ethical and legal issues of BI implementation
Explore emerging technologies and trends in BI
This is a single 10-credit module course. On successful completion of this module, a student will be able to:
Examine BI concepts, processes and technologies.
Produce a plan for the application of BI for decision support and process improvement in a business environment.
Assess the concepts, processes and recommended use of organisation memory to store data.
Critically analyse data using data mining, text and web mining techniques.
Evaluate and use reporting and visualization tools to visualise data to support and improve decision making.
Appraise big data analytics and emerging technologies.
Applicants will normally require an Honours Degree in Computing or equivalent. The course is targeted at IT professionals who would participate in the programme on a part-time basis and complete the programme over two years.
Applicants who don't currently meet the entry requirements may be able to advance their applciation using the Recognition of Prior Learning (RPL) mechanism. RPL allows candidates to make a case that they do meet entry requirements through a combination of formal certified learning and learning through experience (most typically work experience). RPL applications must be made by filling out (please type) the RPL form and submitting it along with supporting documents such as academic certificates and transcripts etc.
Applicants whose first language is not English must submit evidence of competency in English. Please see our English Language Requirements for details.
