Solutions designed for big data can help the oil and gas industry integrate operational analysis with business intelligence so they can optimize processes in order to meet specific business goals. For example, a company might want to determine the best offshore drilling location for maximizing oil
While much of today’s focus on big data is on “smart data,” the power of analytics, the most lasting benefit big data will bring to business worldwide, is agility.
The tools of big data found their genesis in the data-driven startups of Silicon Valley. In Google, Yahoo!, Facebook and Twitter:
Larry Page, CEO of Google, believes in “moonshots.” Not just incremental thinking, but breakthrough progress that makes an order of magnitude difference in a field. At his company's developer conference in San Francisco, Page urged others to do the same: “I'd encourage more companies to do things
Edd Dumbill is VP Strategy at Silicon Valley Data Science and Editor-in-Chief of the peer-reviewed journal Big Data. He’s also an entrepreneur, author, software developer, and chair of Strata conference. formerly was principal analyst at O’Reilly Radar. In a recent article titled “Big Data is
Big data presents important opportunities for enhancing the efficiency, safety, productivity and cost-effectiveness of oil and gas operations. Yet it comes with an array of operational technology challenges that often impede the use of big data for operational gains. For example, companies need
Is data a religion?
I think that’s a ridiculous notion, but it has recently gained credence in the popular mind. Some people seem to believe that a powerful elite regards data-driven management as an absolute faith. Here, for example, is a Washington Post article arguing that the current president
The petroleum industry is no stranger to large volumes of data. Operating in arguably the original sensor-based industry, oil and gas companies have for decades used tens of thousands of data-collecting sensors installed in subsurface wells and surface facilities to provide continuous, real-time
It turns out, borrowing key concepts from legendary business management gurus can play an important role in developing your big data strategy. Big Data Evangelist James Kobielus shares some of his favorite kernels of wisdom from the experts.
Big data is still relatively new with many organizations, and its significance in business processes and outcome has been changing every day. Here are some of the key best practices that implementation teams need to increase the chances of success.
1. Gather business requirements before gathering
Within a few days of one another, IBM CEO Ginni Rometty shared her 3 Principles of Change at the Council on Foreign Relations, and the Wall Street Journal published a special series on big data and how it is changing the equation for business. This blog post reviews the key thoughts behind both
Most organizations today still treat data as a raw material to be mined, with industrial processes for staged production. Your data isn’t an asset you lock up in a vault and protect long past its relevance. It is a product you combine with others, market and sell, buy and trade, to generate new
Big data can’t prove its business value if it remains in a perpetual proof-of-concept phase. How can you prepare your big-data deployment for delivery into a production IT environment? What exactly does it mean to say that big data, or any IT initiative, is truly production-ready? James Kobielus
For energy & utilities firms, big data is not software or a product or even a technology. It’s a business strategy - a long-term, executive-level commitment to treat information as a strategic asset with IT providing the resources needed to bring it to life.