Are big data and machine learning methods enough? Part 1


Sir David Hand gave a brilliant plenary talk and set the stage for a great panel discussion by cautioning us to remember that thinking is required and to be aware of all the dark data out there -- the data that we don't see, but that we need to take into account. Dark Data: Why What You Don't Know Matters is his latest book (see a blog post about it; if you haven't read it, you can get a sample excerpt). The panelists included Cameron Willden, statistician at W.L. Gore, who supports engineers and scientists across many different product lines; Sam Gardner, founder of Wildstats Consulting, with more than 30 years of experience doing statistical problem solving for government and industry; and JMP's Jason Wiggins, a 20-year US Synthetic veteran with expertise in process optimization, measurement systems analysis and predictive modeling/data mining. We ran out of time before we could answer all the questions from the livestream audience, but our panelists have kindly agreed to provide answers to many of them, further sharing the wisdom from their collective experiences. The questions are grouped by topic -- there were so many, we are doing two posts.