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This course covers key principles and practices related to the use of business intelligence (BI) systems to support strategy and decision-making. Topics include performance dashboards and data visualisation; descriptive, predictive and predictive analytics; data, text and web mining; future trends and directions. Real data-sets and industry-standard tools will be used to demonstrate key principles of BI and to help students develop analytical and problem-solving skills related to BI solutions.
Business Intelligence (BI) Systems use various technologies, processes and applications to analyse operational, social and other data (e.g. structured and unstructured, internal and external data) and identify patterns, trends and relationships that can be used to support an organisation’s business objectives and managerial decision making. The term ‘business intelligence’ describes both the product and the process by which organisations obtain, analyse and distribute ‘business intelligence’. The course tackles business intelligence and analytics from both practical and theoretical aspects. Students will be exposed to relevant concepts and approaches of BI and BA and gain experience in developing data-driven solutions to practical business problems.Students completing this course will have a thorough understanding of BA and BI related subject matters, and develop skills in processing and interpreting business data independently for practical solutions, including data understanding, data handling, data visualisation, trend prediction, regression model, simple machine learning and apply these to decision-making.
At the end of this course, it is expected that students will have gained an understanding of key BI concepts, and practical approaches to dealing with data-driven business problems. Specifically, it is expected that students will be able to: Demonstrate an understanding of key business analytics concepts, tools and techniques. Recognise and analyse business problems, issues and opportunities related to the role and use of business data in organisations. Select and apply suitable techniques (e.g. prediction and classification), extract meaningful insights from various data, and make recommendations that align with the organisation’s context/objectives and business decisions.Produce appropriate information models and reports for business decision-making using relevant programming and visualisation tools Work as a team to perform key activities related to the analysis of data and business decisions and provision of meaningful insights (BI) and evidence-based recommendations
This course will provide students with an opportunity to develop the Graduate Attributes specified below:
Critically competent in a core academic discipline of their award
Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.
Employable, innovative and enterprising
Students will develop key skills and attributes sought by employers that can be used in a range of applications.
Biculturally competent and confident
Students will be aware of and understand the nature of biculturalism in Aotearoa New Zealand, and its relevance to their area of study and/or their degree.
Engaged with the community
Students will have observed and understood a culture within a community by reflecting on their own performance and experiences within that community.
Students will comprehend the influence of global conditions on their discipline and will be competent in engaging with global and multi-cultural contexts.
(1) INFO123; and (2) 45 points at 200-level or above RP: STAT101
Lecture slides, example codes, handouts, article links, research articles and reading materials shared on LEARN.
Domestic fee $892.00
International fee $4,563.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
This course will not be offered if fewer than 10 people apply to enrol.
For further information see
Department of Accounting and Information Systems on the
departments and faculties