An important ingredient for any successful business is its staff. And yet recent research shows that human resources ranks lowest among front office operations when it comes to using predictive analytics, particularly to recruit and retain the right professionals for the right positions. But that
Smart predictions can spell the difference between whether your company succeeds wildly or falls by the wayside. Get the details on four strategic pillars for smart, proactive business through predictive analytics deployment in a series of new blog perspectives.
Learn how the UNC Health Care System developed an advanced care insights solution to convert unstructured data into useful alerts and reports designed to help physicians and patient care managers enhance patient care while cutting readmission rates.
Inaccurate perceptions of predictive analytics are common in the business world. In reality, predictive analytics is straightforward to understand, can leverage existing skillsets in business and IT organizations, and can deliver value in most industries and lines of business. Getting started with
A recently released infographic aids in understanding how big data capabilities map back to enterprise strategic imperatives. I'll break this infographics down into steps and discuss each level for clarity and definition.
"Anyone who makes assertions and is unwilling to engage in a discussion or provide evidence for what they say, is probably someone who doesn't really know what they're talking about. Be very skeptical."
That's the advice from Tom Deutsch, program director of big data and analytics at IBM. In this
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
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
As I wrote in Part 1 of this blog series, big data and analytics can help companies develop the “digital oilfield”— integrated operations that unite operational technology (OT) with information technology (IT) to improve decision making and enhance operational and business performance. Adding
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