Big data is a process of using conventional data mining and handling techniques when we are not able to reveal the visions and meaning of the essential data. A relational database is not able to processed unstructured, time-sensitive, and simply large data, because it involves a unique processing approach called big data, which uses monolithic parallelism on readily available hardware. With respect to human deportment and interaction, big data is an assortment of massive quantities of information sets that are examined computationally to uncover patterns, trends, and associations.
According to present technologies, it is possible to examine any data and obtain answers with lesser efforts. This chapter focuses on the emergent body of machine learning (ML) algorithms applied to various big data sources in a business context and recognizes methods, approaches, and tools used to transmute the large amount of patronage data available into valuable information and support business decision making by applying machine learning algorithms. This chapter also focused on the latest technologies used in Hadoop platforms, such as ZooKeeper, Pig, and others.