Insights 2017-11-01T14:18:04+00:00

INSIGHTS

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3 Reasons Companies Need to Adopt Predictive Analytics

Data is growing at a rate of 2.5 quintillion bytes of data being created every year and organizations are drowning in numbers, facts and figures. In fact, most organizations do very little with data, yet wax confident that data is their greatest competitive advantage.

7 Questions with Dr. Eric Siegel

Everyone is talking about predictive analytics, artificial intelligence and machine learning. But these buzz words can be overwhelming to the average subject matter expert (SME), who before the world of big data just wanted to do his or her job. In the information age, SME’s have to be more strategic, effective and efficient.

DMWay and Integrant Analytics Announce Strategic Partnership

Integrant to leverage DMWay’s Predictive-Analytics platform to provide quicker and more effective predictive solutions for the US energy industry April 7, 2017 ------- Integrant Analytics recently announced it has selected DMWay predictive analytics platform and will harness the technology to provide exceptional accuracy in its predictive models for North American energy producers and utilities.

The Black Sheep of Data Science

My data scientist colleagues all get excited about the science of the analytical process. The goal is competing – sometimes with themselves! – to achieve the best model they can get. The process looks like this: Gather the best data set one can get that best fit the business problem. Often, this involves merging dozens of pre-existing data sets, making the process take weeks … if not months and, in some cases, years. Use this data to create the first model. But my data scientist friends are never satisfied. Instead, they are constantly trying to improve the model using machine learning algorithms that no business person understands.

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