Introduction to Data Analytics

Abstract

Recent advances in computing have lead to diverse applications in wide domains such as cyber-forensics, data science, business analytics, business intelligence, computer security, Web technology, and Big data analytics. Data analytics refer to broad term where many of the areas such as cyber-physical systems (CPS), Internet of Things (IoT), Big data, machine learning and data mining overlap among each other. However, there are subtle differences among these areas. Data analytics form as one of the key components of these wide areas in computing. For example, in IoT the data that are collected from various devices need to analyze for inferring the outcomes of it. Hence, data analytics need to be carried on it. There are various platforms available for data analytics. In this chapter, a brief overview of the term data analytics, different types of data, different types of analytics, and the analytical architecture is first discussed. It is later followed by the different phases that are involved in the lifecycle of the data analytics project and the interconnection of Big data and Hadoop ecosystem.