Big Data, Data Science, and Data Analytics: What are they?
Big Data, Data Science, and Data Analytics are not just some technical jargons but are significant concepts contributing to the field of technology. While these terms are interlinked, there is a huge fundamental difference between them.
Big Data refers to a huge volume of data of various types, i.e., structured, semistructured, and unstructured. This data is generated through various digital channels such as mobile, Internet, social media, e-commerce websites, etc. Big Data has proven to be of great use since its inception, as companies started realizing its importance for various business purposes. Now that the companies have started deciphering this data, they have witnessed exponential growth over the years.
Data Science deals with the slicing and dicing of the big chunks of data, as well as finding insightful patterns and trends from them using technology, mathematics, and statistical techniques. Data Scientists are responsible for uncovering the facts hidden in the complex web of unstructured data so as to be used in making business decisions. Data Scientists perform the aforementioned job by developing heuristic algorithms and models that can be used in the future for significant purposes. This amalgamation of technology and concepts makes Data Science a potential field for lucrative career opportunities. McKinsey once predicted that there will be an acute shortage of Data Science Professionals in the next decade.Click Here
Data Analytics seeks to provide operational insights into complex business situations. Looking into the historical data from a modern perspective, finding new and challenging business scenarios and applying methodologies to find a better solution are the prime concerns of a Data Analyst. Not only this, but a Data Analyst also predicts the upcoming opportunities which the company can exploit. Data Analytics has shown such a tremendous growth across the globe that soon the Big Data market revenue is expected grow by 50 percent.