ABSTRACT
Big data is a concept used to illustrate the large set of data that is expanding exponentially according to time. This dataset is so huge as well as complex that it is very difficult to store or process it with any of the conventional tools of data management. The 5V’s related to big data are volume, velocity, variety, variability, and value. The 5V’s make data management technique as well as analytics very challenging for conventional data warehouses. Data mining refers to extracting information and knowledge from huge amount of data. It is one of the computational techniques to find out patterns in huge collection of data sets comprising techniques intersecting artificial intelligence, machine learning, statistics, as well as database systems. One of the main motives behind data mining techniques is to extract knowledge from a given data set and convert it into an apprehensible design that can be used for further use. This chapter introduces the characteristics, types, and usage of big data technique and also discusses the data mining techniques to improve data quality. Data mining technique is one of the most essential sources of knowledge and it requires immense quality data. Data mining approach is used to discover new patterns to store the data. Data mining is used in every sector like business, agriculture, and marketing. There are many data mining techniques such as clustering and classification that can be applied on the dataset to construct new platforms to enhance the performance of existing dataset and help promote the new forecasts on the dataset.
