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Machine Learning
Andrew Pease 0
Towering Insights

The benefits of big data often depend on taming unstructured data. However, in international contexts, customer comments, employee notes, external websites, and the social media labyrinth are not exclusively written in English, or any single language for that matter. The Tower of Babel lives and it is in your unstructured

Brooke Fortson 0
Meet your SAS #StrataHadoop Team: Patrick Hall

The epicenter of big data moves to New York City on September 29 at Strata + Hadoop World. It’s a great chance to mix and mingle with people that live and breathe analytics, including a core SAS team of thought leaders, developers and executives. We’d love to be a part

Charlie Chase 2
You can no longer hide behind MAPE!

There are four key areas that require continuous investment in order to become demand-driven: people, process, analytics, and technology. However the intent of your demand forecasting process along with business interdependencies need to be horizontally aligned in order to  gain sustainable adoption.  Adoption alone doesn't necessarily mean it will be sustainable.       As

Andrew Pease 0
Enter the data composer

Along with the data scientist hype, analytics and the people who make them work have found themselves in the spotlight. The trend has also put an emphasis on the "science" aspects of analysis, such as a data focus, statistical rigor, controlled experiments and the like. Now, I’m not at all against adding more

Data Visualization
Ian Jones 0
Time for VirtualOil 2.0?

Since our last VirtualOil update in May, oil prices have continued to take a beating. As the chart of the rolling five-year portfolio shows, much of our strip of options is now out-of-the-money and the average value per barrel of that optionality has sunk below $7. No surprise then that

Internet of Things
Stuart Rose 0
Flipping the data equation

Big Data has become a technology buzzword. But how is Big Data changing insurance? Historically, insurance companies have used SMALL data to make BIG decisions. Today, insurers are using BIG data for SMALL decisions. What does this mean? Traditionally, insurance companies have aggregated data to group risks into broad categories

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