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Big Data

What do you mean by Big Data?

Big Data refers to large and complex datasets that cannot be processed using traditional data processing applications. Big data analysis challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy, and data sources.

Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time.

Components Of Big Data

Key components of Big Data analysis include data preprocessing, data mining, machine learning, and visualization. By analyzing Big Data, organizations can uncover hidden patterns, optimize processes, and make data-driven decisions to drive innovation and competitive advantage.

Big Data In Academia

In academia, Big Data is studied within the fields of computer science, statistics, and data analytics. Researchers investigate techniques for capturing, storing, and analyzing big data to extract valuable insights and identify patterns, trends, and correlations.

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Frequently Asked Questions On Big Data

What do you mean by big data?

Big data refers to the large, diverse sets of information that grow at ever-increasing rates. It encompasses the volume of information, the velocity or speed at which it is created and collected, and the variety or scope of the data points being covered.

Why use big data?

Big data analytics helps organisations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers.

What are the examples of big data?

Big data comes from myriad sources, including transaction processing systems, customer databases, documents, emails, medical records, internet clickstream logs, mobile apps, and social networks.

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