Big data vs data science. What is the difference between Big data and Data science? What is big data? What is data science?
Data is everywhere. The amount of digital data that exists is rapidly increasing, doubling every two years, and changing the manner in which we live. Information is all over the place. Till the year 2020,about1,7 megabytes of new information will be generated every second for every human being.
Here we will differentiate, big data and data science with various parameters. Before we start Big data vs Data science, let us see each one in detail.
Big data is a humongous volume of data which cannot be effectively processed with the traditional apps that exist. The processing of Big Data starts with the raw data that isn’t aggregated and is generally difficult to store in the memory of a single computer. A popular expression that is utilized to describe massive volumes of data, both unstructured and structured, Big Data inundated a business on an everyday premise. Big Data is something that can be used to examine insights that can prompt better decisions and strategic business moves. By the definition- Big data is high-volume and high velocity or high variety information asset that demand cost-effective, innovative forms of information processing that allow enhanced insights, decision making and process automation.
Managing unstructured and structured data, Data Science is a field that involves all that is related to data cleansing, preparation, and analysis. Data science is a combination of programming, problem-solving, statistics, mathematics, the ability to look at things in a different way, getting data in ingenious ways, data cleaning, aligning and preparing. In simple words, it is an umbrella of techniques that use to extract insights and information from data.
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