Why Data Analytics?
The rapid developments in information and computer technologies have enabled the generation, storage and processing of big data that was out of reach a few years back. Big data is believed to be the key to the next wave of management innovation, productivity, and growth. However, there is a shortage of professionals who can glean meaningful insights from data to make effective decisions. Canadian Business (2015) reports that in spite of the increase in the number of data professionals in Canada, 53% of large Canadian organizations identified the lack of talent as the biggest impediment to successful completion of big data projects. A 2011 report by the McKinsey Global Institute indicates that the United States alone could face a shortage of 1.5 million managers and analysts who have the knowledge and expertise to take full advantage of big data and make faster evidence-informed decisions.
What is Data Analytics?
Data analytics enables managers to enhance traditional descriptive analytics of explaining what has happened with predictive analytics to foresee what will happen under various future scenarios, and with prescriptive analytics to design best policies and actions under all circumstances. Predictive and prescriptive analytics enable companies to transform insight into foresight and most importantly make transformative decisions to significantly improve business performance.
Why Management Sciences?
Management Sciences is a multidisciplinary department with expertise in Information Systems, Applied Operations Research and Statistics, and Management of Technology. Information Systems faculty have expertise in large scale data processing, data mining, databases, human computer interaction, data visualization, text analytics, and search engines. Operations Research and Statistics faculty have expertise in statistical modeling and simulation, forecasting, stochastic modeling, decision making under uncertainty, and optimization. Management of Technology faculty have expertise in behavioural aspects of social media and human-generated data.
Specialized Courses
The Department of Management Science and Engineering can leverage the strengths of its different areas to offer fundamental courses in data analytics that cover all three important categories of analytics:
- Big Data Analytics: Exploring analytics techniques, with the aim of separating signal from noise to best understand past behaviour and take advantage of the big data.
- Statistical Methods for Data Analytics: Exploring predictive analytics techniques with the aim of modeling the relationships between inputs and outcomes to predict system behaviour under various scenarios.
- Operations Analytics: Exploring prescriptive analytics techniques with the aim of optimizing actions against a complex set of objectives to find best practices, especially in case of new product or service launch.
Opportunity:
- 53% of large Canadian organizations identified the lack of talent as the biggest impediment to successful completion of big data projects.
- The US alone could face a shortage of 1.5 millions managers with the knowledge of analytics.
Importance:
- The 50 most innovative companies of 2014 are three times more likely to rely on Analytics.
- By 2017, 80% of the CIO’s time will be focused on analytics and creating new revenue streams through digital services.
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