Today's organizations must capture, track, analyze and store more information than ever before - everything from mass quantities of transactional, online and mobile data, to growing amounts of "machine-generated data" such as call detail records, gaming data or sensor readings. And just as volumes are expanding into the tens of terabytes, and even the petabyte range and beyond, IT departments are facing increasing demands for real-time analytics. In this era of "big data," the challenges are as varied as the solutions available to address them. How can businesses store all their data? How can they mitigate the impact of data overload on application performance, speed and reliability? How can they manage and analyze large data sets both efficiently and cost effectively?
Posted February 09, 2012