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Data for Good
Jill Dyché 0
Big data, one dog at a time

A few years ago, in the height of my workaholism, I took up a hobby. I go to sketchy neighborhoods around L.A. and hang out with dogs I don’t know. I have a long history of adopting and fostering shelter dogs, often getting them out on their “euth dates.” With

Stuart Rose 0
Back to basics

One of my colleagues often asks me “What’s new in insurance”. For an industry that is risk adverse, change does not come easily. In the past we have discussed innovations concerning telematics, drones, wearables devices and even weather data. However when he asked me last week and I responded that

Machine Learning
Leo Sadovy 0
Neural networks demystified

You’ve likely heard the news that the Google DeepMind “AlphaGo” computer not only beat a human expert at the game of Go, defeating the European Go champion, Fan Hui in five straight games, but also beat the reigning world champion grandmaster, South Korea’s Lee Sedol, 4 games to 1. Go

Advanced Analytics | Data for Good
Alan Cudney 0
Dignity Health demonstrates the power of advanced analytics at HIMSS16

According to Lloyd Dean, president and CEO, "At Dignity Health, we are committed to developing partnerships and opportunities that harness the tremendous potential of technology, from improving the patient experience to providing caregivers with tools that will support their day-to-day care decisions." Dignity Health, one of the largest health systems

Advanced Analytics | Analytics
Mike Gilliland 0
Rob Hyndman on measuring forecast accuracy

The new book Business Forecasting: Practical Problems and Solutions contains a large section of recent articles on forecasting performance evaluation and reporting. Among the contributing authors is Rob Hyndman, Professor of Statistics at Monash University in Australia. To anyone needing an introduction, Hyndman's credentials include: Editor-in-chief of International Journal of

Data Management
Bill Davis 0
MapReduce vs. Apache Spark vs. SQL: Your questions answered here and at #StrataHadoop

As the big data era continues to evolve, Hadoop remains the workhorse for distributed computing environments. MapReduce has been the dominant workload in Hadoop, but Spark -- due to its superior in-memory performance -- is seeing rapid acceptance and growing adoption. As the Hadoop ecosystem matures, users need the flexibility to use either traditional MapReduce

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