Big Data Analytics – Virtual Open Class: Making Business Decisions with Clustering Methods (On-Demand Recording)

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Date(s) - 23/01/2021
11:00 pm - 11:30 pm


Data Analytics – Virtual Open Class
Making Sound Business Decisions with Clustering Methods

(On Demand Recording)

This 30-minuteĀ recorded open class will explain how business decisions can be supported with cluster analysis. Clustering enables businesses to classify and segment customers, firms, regions, brands, and products. The classification makes information processing and resource allocations easier in business decisions. The tendency to classify things, however, is not limited to just business decisions and we will see examples of classifications in other scenarios. Real world examples will be used to explain clustering in a business context, followed by an easy-to-understand technical description of the method where clustering is/can be used, followed by methodological approach to clustering. The session will conclude with explaining clustering – personalization as two ends of a spectrum in a grouping/segmentation. Through this discussion, we will also look into clustering in a formal way as part of unsupervised ML techniques.

Instructor: Hemant Sangwan, PhD, MS.

HHemant Sangwanemant Sangwan has 12+ years of industry experience in management consulting, data science & analytics, marketing research, economic consulting & forecasting. He is also an independent consultant & Expert advisor to a B2B startup in AI/Blockchain with focus on financial services. His previous employers include Boston Consulting Group (BCG), GfK Canada, and IHS Markit. Hemant earned a PhD in Management from the Rotman School of Management, University of Toronto and an MS (Quantitative Economics) from the Indian Statistical Institute. Hemant has extensive experience in education and has taught at all levels in post-secondary. He is a full-time Professor at Seneca College, School of Marketing; a sessional lecturer at York University (Schulich School of Business, School of Continuing Studies, SEEC) and he has taught Analytics and Data Science courses at various universities in Toronto.