AFM241 Lecture Notes - Lecture 4: Business Analytics, Machine Learning, Call Centre

• School: University of Waterloo
• Department: Accounting & Financial Management
• Course: AFM241
• Professor: Theophanis Stratopoulos

Document Summary

Moneyball : combat biases using data analytics. Ted talk kenneth cukier analytics in our world: new idea: individual choice vs household choice affect buying choice, data analytics was able to measure that. Big data vs old, small data. features: fluid and dynamic vs static and stationary, sharing, processing, copying. Area of machine learning: machine learning examples: self-driving cars, computer checkers, interpreting biopsy: machine learns by collecting data, challenge in big data: safeguarding human rights, loss of white collar jobs, privacy, misuse of data: police predicting. Volume: storage costs are low, new issue: how know what is relevant from the large data volume. Velocity: how fast is the data streaming in. how do we react to it: unprecedented speeds. Variety: type of data you get: structured data, unstructured data: examples email, texts, videos and audio. Integrity: how to check that data integrity is strong so you can rely on it, challenge: with language difference.