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Why Data Science Is So Crucial In The Current Age Of Big Data?

Data Science is one of the rapidly evolving fields in the current age of Big Data.  Data Science is an incorporation of Computer Science, Artificial Intelligence, Machine Learning, and mathematics in order to discover useful information which is encrypted inside large volumes of unstructured, structured, and semi structured data sets. Data Science can be broadly defined as a methodology that integrates the skills of statistical computing and data analytics to make accurate interpretations out of Big Data.

Data science is in existence from a long time and is being used for decision support, data storage and retrieval, data optimization, social network analysis, and Business Intelligence, Predictions and more.

Why Data Science Is So Crucial?

Data science includes a number of sub disciplines, including statistical techniques, artificial intelligence (AI), computer science, web analytics and systems, distributed systems, and visualization. These subdisciplines are inter-related and depend on each other for successful application. Data science can be used to improve the quality of data that a company obtains from external sources and helps them in extracting the information encrypted deep inside the data & converts it into actionable insights. Data science can also be used to create new data storage systems.

Data science is a process, not a tool, and it does not follow that a solution will emerge overnight. It takes considerable time, effort and commitment. Although, there are many cases where a single technique has made a significant difference in an organization, the benefits and drawbacks of each technique vary widely. Data Science is constantly evolving in its application in all industries, as the field continues to develop.

Applications Of Data Science:

Data Science is used for a number of applications in the fields of information technology, biomedicine, engineering, healthcare, retail, financial institutions, and consumer products. This includes large-scale and high-volume manufacturing operations, medical research and development, educational institutions, government agencies, and consumer product companies.

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