Big Data is one of the buzzwords in the BI world in recent times. In fact, it is the reason of next frontier for innovation, competition, and productivity. There are quite a few vendors who started to claim for providing a tool that can handle Big Data.
SO, what are big data?
Big data is a term applied to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Big data sizes are a constantly moving target currently ranging from a few dozen terabytes to many petabytes of data in a single data set.
Examples of big data
Examples include web logs; RFID; sensor networks; social networks; social data (due to the Social data revolution), Internet text and documents; Internet search indexing; call detail records; astronomy, atmospheric science, genomics, biogeochemical, biological, and other complex and/or interdisciplinary scientific research; military surveillance; medical records; photography archives; video archives; and large-scale eCommerce.
Big data analytics
Big data requires exceptional technologies to efficiently process large quantities of data within tolerable elapsed times. Technologies being applied to big data include massively parallel processing (MPP) databases, datamining grids, distributed file systems, distributed databases, cloud computing platforms, the Internet, and scalable storage systems.
These are still early days to say any breakthrough technology that can answer industry requirement to handle Big Data. However there is some sunshine coming from solutions such as Apache Hadoop. |
