Data Analytics is the practice of using data to drive business strategy and performance. It includes a range of approaches and solutions, from looking backward to evaluate what happened in the past to looking forward to do scenario planning and predictive modelling.Data Analytics spans all of the functional businesses to address a continuum of opportunities in Information Management, Performance Optimisation and Analytic Insights. Organizations now realize the inherent value of transforming these big data into actionable insights. Data science is the highest form of big data analytics that produce the most accurate actionable insights, identifying what will happen next and what to do about it.
Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs. Hadoop is not just an effective distributed storage system for large amounts of data, but also, importantly, a distributed computing environment that can execute analyses where the data is.
In this course, detailed explanation about hadoop framework and its ecosystems has been provided. All the concepts are explained in detail with examples and business use cases as case studies.Also, latest technologies in big data area like apache spark, apache kafka, Mongo DB are explained. In addition, Interview questions with respect to each ecosystem and resume preparation tips are included.