A Research on Big Data Analysis & Processing With Data Mining Techniques

Bharati Punjabi, Honale Sonal
2015 International Journal of Scientific Engineering and Applied Science (IJSEAS)   unpublished
Today increasing number of organizations are facing the problem of explosion of data and the size of the databases used in today's enterprises has been growing at exponential rates. Data is generated through many sources like business processes, transactions, social networking sites, web servers, etc. and remains in structured as well as unstructured form. Today's business applications are having enterprise features like large scale, data-intensive, web-oriented and accessed from diverse
more » ... from diverse devices including mobile devices. Processing or analyzing the huge amount of data or extracting meaningful information is a challenging task. The term "Big data" is used for large 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 peta bytes of data in a single data set. Difficulties include capture, storage, search, sharing, analytics and visualizing. Typical examples of big data found in current scenario includes web logs, sensor networks, satellite and geo-spatial data, social data from social networks, 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.
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