• DR R. PARIMALADEVI
• Dr.S.Mohandass

Big data sizes are constantly increasing, currently ranging from a few dozen tera-bytes (TB) to many petabytes (PB) of data in a single data set. Consequently, some of the difficulties related to big data include capture, storage, search, sharing, analytics, and visualizing. Today, enterprises are exploring large volumes of highly detailed data so as to discover facts they didn’t know before. Analytics based on large data samples reveals and leverages business change. However, the larger the set of data, the more difficult it becomes to manage. Naturally, business benefit can commonly be derived from analyzing larger and more complex data sets that require real time or near-real time capabilities; however, this leads to a need for new data architectures, analytical methods, and tools.

Big Data, E commerce, DataAnalytics

"BIG DATA IN E – COMMERCE ANALYTICS : AN OVERVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 3, page no.1476-1480, March-2020, Available :http://www.jetir.org/papers/JETIR2003219.pdf

"BIG DATA IN E – COMMERCE ANALYTICS : AN OVERVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 3, page no. pp1476-1480, March-2020, Available at : http://www.jetir.org/papers/JETIR2003219.pdf