I was recently listed as one of the top Big Data/Data Science leaders on LinkedIn by KDnuggets. I was delighted to be on the list and to share it with some great thinkers and writers.
My interest, as regular readers of the blog will know, is not really on how you build analytic models or apply data science techniques to Big Data (or small data for that matter). My focus is on how you make sure that the analytic models you build, the data science you do, impacts the business. How do you make sure that your data science focuses on the right business problem and will be fit for purpose when you are done? And how do you make sure you can make the organizatonal and system changes necessary to adopt it when you are done. Recently I wrote this post on the broken links in the analytics value chain to set out the problem.
Our experience is that decision modeling, especially decision modeling using the new Decision Model and Notation (DMN) standard, is an essential tool for data science/data mining/predictive analytic projects. If your problem is at the beginning of the value chain, specifying business understanding correctly, check out this post on framing the problem using decision modeling or download this brief, 6 Questions To Ask Your Business Partner Before You Model. If your problem is not getting the business problem framed correctly but actually getting it deployed, then check out this post on operationalizing analytics or download the brief 5 Things You Need to Know Before You Deploy Your Model.
Regardless I hope you will follow me on LinkedIn and reach out if you have questions or if we can help.