Data Science in Action – Practical Use Cases that Demonstrate how Businesses Generate Value from Data 

Slides (PDF, 7.0 MB)(PDF 7,2 MB)

Abstract - This presentation will give several examples of how some of the standard techniques of machine learning can be applied to solve real-world business problems.  In particular, we will look at recommendation engines, processing machine-to-machine data and predicting customer behavior, in industries as diverse as telecommunications, financial services, retail, automotive and aviation.

These analytical tasks are enabled by the Pivotal platform, which allows capturing and processing large, complex and fast-moving datasets.  The presentation will show how insights gained from data can be turned into predictions, which in turn can be turned into prescriptions for business success.

Biography - Michael Natusch heads Pivotal’s Data Science services in EMEA. His experience lies in predictive analytics and he has worked on a wide variety of assignments such as customer churn reduction, customer proposition optimization, pricing, HR analytics, logistics and supply chain optimization and also more industry-specific issues such as telecoms network deployment optimization and health insurance claims optimization. Michael holds a PhD in theoretical physics from the University of Cambridge and an MBA. He is a Fellow of the Royal Statistical Society and lectures at the Open University.