Telecommunications is a necessarily data-driven and capital-intensive business. Mobile network rollouts and the increasing use of mobile devices and social media generate huge amounts of customer and market data. Quick responses to changing market conditions are imperative to remaining competitive.
Data is growing and moving faster than healthcare organizations can consume it, yet getting insights from that data into the hands of practitioners can quite literally make the difference between life and death.
Financial services and banking are data-driven. Organizations in these industries store and analyze data on millions of customers, this data valued in the billions. As a consequence, they have to struggle with ever increasing volumes, velocity and variety of data. To stay ahead of competition, and
Today, energy and utility companies are relying on Hadoop to help curb energy consumption, reduce energy loss and add more clean power to the grid. Using big data and analytics, organizations can empower users to understand their energy usage and give them the chance to reduce how much they use and
Automotive and manufacturing organizations deal with a massive volume of data, including global data from customers and data generated through internal business operations, research and development (R&D) and supply chain activities. These data sets represent an opportunity for an organization
Big data (data from many sources, of varying formats, both structured and unstructured) means different things in different industries. But as different as their needs and usage of big data may be, there is one commonality among all industries: the opportunity to plumb big data for better, more
On Thursday, April 3, I had the pleasure of moderating a video-streaming web roundtable in which panelists discussed the transformational applications of big data analytics. The panel included big data solution providers and experts, and we discussed everything from big data applications and