June 04, 2014
Finding a Big Data "Safe Space" for the Energy Sector
The oil industry was one of the original "smart" industries, but its tradition of leadership in using data to improve operations, enhance security and serve markets has been diminished over time by the counterintuitive incentives imposed by regulators.
As the sector transforms in response to a supply-side revolution and prepares to engage with global markets more directly through exports, the industry should be freed to build the next generation of infrastructure with efficient markets, security and consumer needs in mind.
One of the satisfying things about working in the oil business is how real it is: an actual physical substance is extracted, chemically upgraded and put to use every day in the real world by real people. That means it can be easy to forget how much the oil sector has relied on data collection and analysis to drive efficiencies that have served consumers well, and how a change in methods of collection and analysis can alter the way efficiencies are identified, implemented and achieved.
More from CNAS
-
The Trouble with America’s Oil Deal in Venezuela with Francisco Monaldi
Podcast
Energy expert Francisco Monaldi joins Emily and Geoff to discuss the U.S. government’s unusual oil deal in Venezuela. They get into the decades of missteps and corruption that...
By Emily Kilcrease & Geoffrey Gertz
-
What Will the Latest Trump-Xi Summit Bring? Four Experts Set the Stakes.
Commentary
Both leaders want a big show, and their teams are going through the motions of staging one....
By Liza Tobin
-
Not the Best Place to Resolve Conflict, BRICS Summit Shows How Countries Are Hedging: Expert
Video
Rachel Ziemba, adjunct senior fellow at the Center for a New American Security, joins CNBC's Squawk Box Asia to discuss why some BRICS countries may be the next target of U.S....
By Rachel Ziemba
-
How China Is Stealing America’s AI
Commentary
Sometimes the fingerprints are obvious: Kimi K3 has identified itself as “Claude,” Anthropic’s model; it was trained on so much of its rival’s output that it mistakes itself f...
By Liza Tobin
