Oil and gas data management overview

In the oil and gas industry, analytics are used to improve both upstream and downstream operations, from optimizing exploration and forecasting production to reducing commodity trading risk and understanding customer's energy needs. If you plan to derive value from the digital oil field, big data, and analytics, one of the first things [...]

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Analytics and Hadoop partnering for success

In a complicated, fast-paced and connected world, you don’t succeed alone.  SAS and Cloudera have a successful  partnership that dates back several years. Our products are complementary and provide significant quantifiable value to customers who run them on the same cluster.  Add Intel to the mix and you have a trio [...]

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Machine learning in action today

What's that productivity related quote by Charles Dickens? "My advice is never do tomorrow what you can do today." For years, machine learning has been written about and discussed widely with a focus on the benefits it will bring in the near future. But guess what? The future for machine learning [...]

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From downtime to upside with oilfield predictive maintenance

Dust off that old aphorism about an ounce of prevention. Oil companies applying analytics for predictive maintenance can see a substantial downtick in the unanticipated equipment repairs that quickly eat into an oil well’s profitability. Maintenance is far from a trivial concern in the oilfield. A pumping oil well is [...]

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Surfing big waves

I just spent much of the past week watching and trying to ride waves on the North Carolina coast. Small waves, mind you, nothing spectacular and certainly nothing that you would consider edgy or life-altering. Nothing that big wave surfers like Laird Hamilton, Garrett McNamara and others of their substance [...]

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What’s the future of analytics within the enterprise architecture?

What does the future of analytics look like in your organizations enterprise architecture? Does it include thinking about a two speed approach to analytics which includes both: An agile rapidly changing analytics platform for innovation (a lab) seperated from operations and broad enterprise audience usage A slowly moving systematic enterprise analytics platform (a factory) [...]

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Build a culture that embraces big data challenges

Big data. Streaming data. Complex data. We’ve all heard the reasons why organizations feel like they’re facing an insurmountable data challenge. Now, it’s time to do something about it. For the past few years, SAS has helped some of the world’s leading companies make sense of an avalanche of data. [...]

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UK Hadoopists: fashionably late to the big data party

People are such an important aspect of data analytics. I was reminded of this at the recent Strata+Hadoop World event, where I saw first hand that the UK is indeed facing the same skills gaps as elsewhere in the world. Perhaps that didn’t surprise me, but I also noticed the [...]

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Self-service BI and approachable analytics for all

Still think business intelligence (BI) and analytics are only for big companies? The truth is, small to medium size enterprises (SMEs) can benefit from BI and analytics in a big way. Digital disruption Thanks to innovative new developments SME’s (and small teams who haven't yet gotten IT’s attention) can now [...]

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The pros and cons of innovation labs

How is it that some companies can come up with a big idea and implement that idea successfully in the market, while others never get past the idea phase? "In the case of innovation," says Jill Dyché, VP of SAS Best Practices, "big ideas aren't enough." It's also not enough [...]

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