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Business analytics enables organisations to make quicker, better and more intelligent decisions to create business value in the broadest sense - potentially the difference between survival and extinction in an increasingly competitive world. Evidence-based decision-making supported by a data-driven culture is essential to the management of organisations.

Davenport and Harris (2007) define business analytics as 'the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions'. A key aspect of this definition is that analytics ultimately provides insight that is actioned - not just descriptions (e.g. customer segmentation) or predictive models (e.g. which customers are likely to churn). Analytic methods are being used in many and varied ways - for example, to predict consumer choices, to predict the likelihood of a medical condition, to analyse social networks and social media, to better manage traffic networks. There are many ways of creating value from data, especially when an organisation's internal data is combined with external and open data.

This course addresses the context of business analytics and the management actions required for organisations to manage business analytics such that they can create value from their data and make progress on the transformational journey to becoming data-driven. The course comprises three core areas: (1) managing data and sources of value, (2) the business analytics process, (3) navigating the organisational context.

As part of the business analytics process, you will build predictive models. This requires a basic understanding of statistics and therefore you will be required to study the material on regression provided by the Harvard Quantitative Methods online course during the first five weeks of the course. Information about the Harvard course and how to enrol in it will be provided to you in Moodle. Your regression knowledge will be assessed by a multiple-choice quiz.

Study Level


Offering Terms

Term 1, Term 3



Delivery Mode

Fully online

Indicative contact hours


Conditions for Enrolment

Must be enrolled in Program 8355, 8625, 8616, 5950, 5457, 7315, 7333, 8345 or 8350

Course Outline

To access course outline, please visit:


Pre-2019 Handbook Editions

Access past handbook editions (2018 and prior)

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