Adaptation of Artificial Intelligence in Big Data Mining and its Impact: A Study

Abstract

Continuing progress in data mining contributed in many forms of algorithms, taken from the areas
of database and statistics, artificial intelligence and pattern recognition, which is utile for technology use and
adaptation. Data mining is primarily used today by businesses to collect knowledge about their products,
clients, marketing campaigns and other affecting aspects.
The businesses can figure out correlations among the ‘external item including consumer demography and
economic indicators etc. and ‘internal' elements such as product positioning, personnel skills and price etc. by
using Data mining.” Data mining is the growth of an area with an extensive history. The innovation of word
takes place in 1990s. The origin of Data mining is vestige back by the side of three unit lines. First is the
artificial intelligence, second is the statistics and third is the machine learning. Artificial intelligence (AI) is
based on heuristics; it tries to utilize human like thinking procedure to statistical jobs. Lots of high-end business
products utilize various artificial intelligence techniques, for example, relational database systems utilize query
optimization technique. Statistics acts as the base for the numerous data mining techniques, for example,
“standard variance, regression analysis, discriminate analysis, confidence intervals, standard deviation,
standard distribution and cluster analysis etc.” These are used to examine the data and their relationships with
AI. This is paper main focus on adaptation of artificial intelligence in big data mining and its impact.