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There are some major differences between Data Science and Big Data: ● Organizations employ big data to improve efficiency, explore untapped markets, and increase competitiveness, whereas data science focuses on offering modelling techniques and procedures to precisely analyse the possibilities of large data. ● Companies can collect massive volumes of data, which is referred to as big data, but data science is required to extract useful information from the data. ● The 3V's of the big data guide dataset and is characterized by velocity, variety, and volume but the data science provides techniques to analyze the data ● Data science employs both theoretical and practical ways to extract knowledge from large amounts of data, and so plays a vital part in realising the potential of big data. Big data, in any case, can be thought of as a collection of data that has no credibility unless it is examined using deductive and inductive reasoning. ● Big data caters to a large amount of data set which is also known as data mining, but data science makes use of machine learning algorithms to design and develop statistical models to generate knowledge from the pile of big data. ● Finally, Big data is more concerned with technology, computer tools, and software, whereas data science is more concerned with business decisions. For more information kindly check our services- Product engineering services companies in USA Artificial intelligence solution providers Computer vision development services Big data engineering companies Data lake consultant