ABSTRACT
This chapter describes the pertinent areas of analytics (data science, data analytics, and Big Data) and relates them to the wider concept of knowledge management. Technology is the driving force behind the creation and transformation of Big Data and data science. Data science uses automated tools and mechanics to extract and relay information to assist individuals and organizations in analyzing their own data for better decision-making processes. The data-driven paradigm raises questions about security, privacy, and storage of data and its resulting information. Data and information visualization is key to the process of making sense of big data and data analytics. The chapter discusses three tools, namely, IBM's Watson Analytics, SAS Enterprise Miner, and Tableau, as they are marketed towards both business and academic sectors, as well as introduce popular open-source coding languages that can be used as alternatives. One of the notable effects of data science and data analytics revolution is that new career opportunities are emerging.
