The Art of Analytical Decomposition

Data Science, Sutton Center / Sutton South (NY Hilton)
Average rating: ****.
(4.25, 4 ratings)

So here you are: You know that there is big data everywhere — including data on every single transaction, service call, and pencil supply order from your company on some server somewhere. You also have least 3 major business issues and a nagging suspicion that for each of them there has to be a better solution. There must be some cool analytical way using all that data to do this – right? There certainly is no shortage of vendors telling you that they have exactly the solution you need, to do all that cool stuff and more with your data. But building a good analytical solution for a staggeringly complex business problem is like designing a pocket watch from scratch. At the heart of the matter is the ability to break the problem into smaller sub tasks and design analytical solutions for every one of them and finally fitting them all back together.

Photo of Claudia Perlich

Claudia Perlich

Dstillery

Prior to joining Dstillery (former Media6Degrees), Claudia Perlich spent five years working at the Data Analytics Research group at the IBM T.J. Watson Research Center, concentrating on research in data analytics and machine learning for complex real-world domains and applications. She has been published in over 30 scientific publications and holds multiple patents in the area of machine learning. Claudia has won many data mining competitions, including the prestigious 2007 KDD CUP on movie ratings, the 2008 KDD CUP on breast-cancer detection, and the 2009 KDD CUP on churn and propensity predictions for telecommunication customers. Claudia received her Ph.D. in Information Systems from Stern School of Business, New York University in 2005, and holds a Master of Computer Science from Colorado University.

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