5 Reasons Over Half of Data Science Projects Never Leave the Lab

Remember dissecting a frog in middle school? The point of the project was to learn about the internal workings of the amphibian’s organs and get a better picture of ecology as a whole. However, the smell of formaldehyde often made it difficult to think about the purpose. Instead, the tendency was to finish the task at hand — one that usually involved a knife-happy partner paired with a squeamish one who documented results with eyes half-shut.

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Oil and Gas Refinery Challenges: People, Product, and Placement

The revival of a strong economic foundation, increase in global demand, and boom of U.S. shale production shine a bright forecast for oil and gas refineries, numbering about 700 worldwide. About 20% of these operate in the U.S. and have emerged as one of the financially healthier players in the oil and gas ecosystem.
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How Prescriptive Analytics Reshapes Fracking in Oil and Gas Fields

Shale oil promises to put the United States back in the lead as an energy superpower. However, while shale oil is abundant, it can be difficult to locate and extract. This is why horizontal drilling and hydraulic fracturing, commonly referred to as fracking, have become common practice. Unfortunately, fracking is incredibly inefficient, as well as harmful to the environment.

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How Prescriptive Analytics Will Reshape Your Refinery Capital Expenditure

As in any industry, in oil and gas production the objective is to maximize production while minimizing overhead. Unlike many other industries, however, oil and gas refineries represent a substantial outlay of capital, so optimizing capital expenditure is critical for maximum return on investment (ROI) and return on assets (ROA).

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Four Best Practices for Tapping the Potential of Prescriptive Analytics

In a world of increasingly complex decisions, competitive growth and unexpected challenges, it’s not surprising that investments in big data, advanced analytics and business intelligence are at an all-time high.
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4 Ways to Maximize Arbitrage Opportunities Using Prescriptive Analytics

Day traders, hedge fund managers, commodity brokers, and energy traders routinely take advantage of market price differences to turn immediate profits. Maximizing an arbitrage opportunity requires precise timing and confidence in your market data, otherwise what looks to be a sure profit could turn into a net loss. That’s why more financial, energy, and commodity traders are relying on prescriptive analytics to ensure their arbitrage profits.

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The New Oil and Gas Quarterback to Climate Change Solutions: Prescriptive Analytics

Most Americans who hear the phrase “Hail Mary” (outside of church) think of football. It  brings to mind a long pass in the last seconds of the game that scores a victory for the team who would otherwise have lost.

In June, the Vatican had its own pep talk for “Team Earth” with oil and gas executives: quit drilling for fossil fuels that cause harm to the environment and impact the world’s poorest. At the event, the Pope emphasized his interest in the renewables strategy, much like a “Hail Mary” for humanity.

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Six Transformational Values Realized from Prescriptive Analytics

Courtesy of our partners over at TBM Consulting!

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Use Prescriptive Analytics to Make Decisions that Will Help Your Company Make More Money

Efficiency Gains and Cost Savings Don’t Always Drop to the Bottom Line. Prescriptive Analytics Can Explain Why and What to Do About It.

How prescriptive analytics can help manufacturers set priorities and realize greater financial gains from capital investments and improvement efforts.

During employee team meetings, the CEO of one of our clients would always make a point of reviewing how the company made money. “We take a bunch of random raw materials,” he would say, “and convert them into something we can sell for more than what it costs to make. What’s left over is called profit. We’re in business to make more of that stuff called profit.”

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Transform the Finance Function with Prescriptive Analytics

"Big data” (a buzz word) is a term that more and more businesses know. It's essentially a term that signifies large and complex amount of data sets — structured and unstructured — that are notoriously hard to process and analyze with traditional applications. What's important isn’t the quantity but what organizations DO with “big data”. A major problem with big data (or data in general) is that companies are not focused on analyzing data for insights; they simply don't know where to start or what to do with it!

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