In today’s increasingly connected world, machine data analysis is becoming a business imperative. While managing it may be challenging, opportunities abound across multiple industries for those who can tackle this complex data.
Harnessing the power of big data and analytics is valuable when conducting competitive analyses. Organizations can search and analyze a range of industry information to identify trends, anticipate changes and uncover emerging opportunities. To use big data in this way, organizations need solutions
This is our fourth post in a series of seven presenting the findings from the IBM Institute for Business Value and University of Oxford’s Big Data study, “Analytics: the real world use of big data in financial services.”
As part of this recently published global research study, my colleagues David
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
Operations Analysis, one of the top five use cases for big data, is about analyzing a variety of machine data to get improved business results. The key is combining machine and business data, which allows you to put insight right into the hands of the operational decision maker. In this videochat,
Here’s a big data problem for you. Let’s say you’ve accidentally traveled back in time 30 years and the only way to get Back to the Future is to transfer 1.21 Gigawatts of energy into a beat-up DeLorean.
Well, back in 1985, the solution, by Hollywood standards of course, was the
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
On a conference call hosted by IBM Information Management General Manager Bob Picciano, over 1000 participants listened to a Q and A led by IBM Vice President Martin J. Wildberger with Kent Collins, database solutions architect, of BNSF Railway. An early tester of DB2 BLU, Kent calls the BLU
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
This week’s Friday Data Flick gives you insight into “operations analysis,” which is one of the top five uses (also called “use cases”) for big data. Operations analysis is about analyzing a variety of machine data to get improved business results. The key is combining machine and business data,
Dr. Michael Kowolenko, Principal Research Scholar, shares how North Carolina State University helps businesses make better decisions and gain insight using IBM big data solutions.
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Join Vijay Ramaiah, product manager for IBM big data, as he discusses the new class of big data applications that are delivering new operational insights by analyzing huge volumes of machine data. This is the third in our series examining popular use cases for big data.
For more examples of
Across industries, companies are finding that a critical factor in their success is the ability to analyze massive amounts of data in near real time. Telecommunications is one of the leading industries that not only creates a lot of data but is also tasked with understanding customer behavior and
Eric Sall, vice president of product marketing for IBM's Information Management Group, joins Wikibon analysts Dave Vellante and Jeff Kelly to discuss real-world big data use cases:
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