The Concept of Data Science in the Era of Big Data
The omnipresence of data in our contemporal world is helping to reshape our world. With the unprecedented rate of data creation, and the increasing role data plays in most of our lives, it is easy to assume that the digital revolution is the most important life-changing event of this era. The high volume, high velocity and wide variety of data generated by the digital revolution are commonly referred to as Big Data. Before, researchers were facing the problem of how to store big data, but now, the main focus is not how to building a framework and solutions to store big data, companies like Hadoop, Hbase, CouchDB, (storage platform that stores structured and unstructured Data) and others have successfully solved the problem of storage, the focus has shifted to the processing of these big data. However, the volume and variety of data have far outstripped the capacity of manual analysis. As data continue to grow in size and complexity, new algorithms need to be developed so as to learn from eclectic data sources At the same time, computers have become far more powerful, networking is ubiquitous, and algorithms that can connect datasets to enable broader and deeper analyses than previously possible. The limitation of conventional statistics to manage and analyze big data has inspired data analysts to venture into data science.. Hence, the concept of data science. Data Science is a combination of multiple disciplines that uses statistics, data analysis, and machine learning to analyze data and to extract knowledge and insights from it. This paper gives general overview of big data revolution, the concept of data science, it uses, it structures, it relationship with other disciplines, application areas and, how it works.