Big data and data science are hot topics that need to be understood today. Confusion between both subjects is quite prevalent as most industries involved in these topics do not agree upon a universal definition for both. The amount of data collected and stored has never happened before. The growing variety and volume of data are alarming, making it critical to understand the concepts of these fields.
Data is digital gold in many ways and is extraordinarily valuable, but this value is realized after the data has been assessed or panned. Data science is very popular and has been used to describe different data-related processes and techniques. Big data is comparatively new as the collected data and the associated challenges require newer and innovative hardware and techniques for handling it. In this article, we will compare big data vs data science and also give brief definitions of both.
What is Big Data?
Big data can be simply defined as larger, more complex data sets from new data sources. It is a special application of data science. The data sets in this application are huge and logistical challenges need to be overcome to deal with them. These data sets are so enormous that traditional data processing software cannot manage them. Big data has become successful in addressing business problems that were previously difficult to execute.
What is Data Science?
Data science is a superset of big data. It uses scientific process, mathematics, statistics, artificial intelligence, specializing programming, and general social observations to observe, uncover and explain niches of business ideas based on the data.
Data science applications are the requirement of the market at the moment. The combination of skills required for data science is very rare which has seen a rise in the demand for data scientists in recent years. According to a 2020 survey by IBM, the number of job openings in the field continues to grow at over 5% every year, and data science career opportunities are piquing everyone’s interests.
Big Data vs Data Science: Analysis
- Data science is a complete area while big data is a technique to collect, maintain and process huge amounts of information.
- Data science is about collecting, processing, analyzing, and utilizing data in various operations. It is a more conceptual subject. Big data is about extracting vital and valuable information from huge amounts of data.
- Data science is more comparable to subjects like Computer Science, Applied Statistics, or Applied Mathematics. However, big data is a technique that tracks and discovers trends in complex data sets.
- Data science mainly uses tools like SAS, R, Python, etc. Big data tools include Hadoop, Spark, Flink, etc.
- Data science is mainly used for scientific purposes. Big data is mainly used for business purposes and customer satisfaction.
- Data science deals broadly with the science of data, while big data deals more with the processes of handling voluminous data.
Both Data science and big data have almost become staples for modern business and strategy. Praxis can be a great chance for you to enroll in a top-notch program with astounding placement records and a well-curated curriculum. Learn more about the curriculum and placement stats of our Data Science Course in Kolkata and Data Science Course in Bangalore.
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