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Dealing with the Data Deluge - Knowledge Discovery and Causal Inference with Bayesian Networks
at the Bentley U Virtual Analytics Symposium;
January 26, 6:00, reception to follow at 7:00;
location Smith 122 at Bentley or remotely by Centra
please email Dominique at dhaughton@bentley.edu if you are planning to attend in person or remotely.
Summary
While economists and social scientists have been using observational data for over a century for policy development, the business world has only recently been discovering the emerging potential of "big data" and "competing on analytics." As these terms are becoming buzzwords, and are rightfully expected to hold great promise, the strictly observational nature of most "big data" sources is often overlooked. While the mantra of "correlation does not imply causation" remains frequently quoted as a general warning, many business analysts would not know under what specific conditions it can be acceptable to derive a causal interpretation from correlation in observational data. Consequently, causal assumptions are often made rather informally and implicitly and thus they typically remain undocumented. Given that the concept of causality remains ill-understood in many practical applications, we seriously question today's real-world business capabilities for deriving rational policies from the newly-found "big data."
With these presumed shortcomings in business practice, it is our objective to provide a framework that facilitates a much more disciplined approach regarding causal inference while remaining accessible to (non-statistician) business analysts and transparent to executive decision makers. We believe that Bayesian networks (and their implementation in the BayesiaLab software package) are an appropriate paradigm for this purpose. We will demonstrate, with an example from the field of marketing science, how Bayesian networks can provide a robust basis for making the (often dangerous) leap from observational inference to causal inference.
Speaker's bio
Stefan Conrady is the cofounder and managing partner of
Conrady Applied Science, LLC, a privately held consulting firm specializing in knowledge discovery and probabilistic reasoning with Bayesian networks. In 2010, Conrady Applied Science was appointed the North American sales and consulting partner of Bayesia S.A.S., the leading provider of software for knowledge discovery, data mining and knowledge modeling using Bayesian networks.
Details, including instructions on how to attend remotely, are available at the symposium web site
atcweb.bentley.edu/conferences/virtualanalytics/