monteza

In information technology, big data^[1][2] consists of data sets that grow so large and complex that they become awkward to work with using on-hand database management tools. Difficulties include capture, storage,^[3] search, sharing, analytics,^[4] and visualizing. This trend continues because of the benefits of working with larger and larger data sets allowing analysts to "spot business trends, prevent diseases, combat crime."^[5] Though a moving target, current limits are on the order of petabytes, exabytes and zettabytes of data.^[6] Scientists regularly encounter this problem in meteorology, genomics,^[7] connectomics, complex physics simulations,^[8] biological and environmental research,^[9] Internet search, finance and business informatics. Data sets also grow in size because they are increasingly being gathered by ubiquitous information-sensing mobile devices, aerial sensory technologies (remote sensing), software logs, cameras, microphones, Radio-frequency identification readers, and wireless sensor networks.^[10][11] The world’s technological per capita capacity to store information has roughly doubled every 40 months since the 1980s (about every 3 years)^[12] and every day 2.5 quintillion bytes of data are created.^[13]

The consumerization of IT offers tremendous opportunity to CIOs possessing the leadership skills and vision to engage substantively with line of business counterparts.
Even the most casual observer of enterprise software can see the growth and importance of cloud computing. For example, SAP’s purchase of SuccessFactors for $3.4 billion and Oracle’s acquisition of Taleo for $1.9 billion make clear that cloud is now part of mainstream enterprise software.
While the growth of cloud is obvious, the impact on IT is less clear. Consider the following chart from a report by the SandHill Group (and sponsored by SAP):