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  1. Data which are very large in size is called Big Data. Normally we work on data of size MB (WordDoc ,Excel) or maximum GB (Movies, Codes) but data in Peta bytes i.e. 10^15 byte size is called Big Data. It is stated that almost 90% of today's data has been generated in the past 3 years.

  2. Big Data refers to a collection of a very large and complicated set of data for which it becomes difficult to process using traditional or manual database management tools. The size of data grows exponentially and is generally in terabytes or more.

  3. Big Data contains a large amount of data that is not being processed by traditional data storage or the processing unit. It is used by many multinational companies to process the data and business of many organizations. The data flow would exceed 150 exabytes per day before replication.

  4. Mar 8, 2024 · Large data volumes that cannot be handled by conventional data management and manipulation technologies are referred to as “big data.” These datasets have a high velocity, volume, and variety and can be structured, semi-structured, or unstructured.

  5. Dec 2, 2022 · Big Data: Big Data basically refers to the data which is in large volume and has complex data sets. This large amount of data can be structured, semi-structured, or non-structured and cannot be processed by traditional data processing software and databases.

  6. Jun 13, 2024 · Summary. What is Big Data? Big Data is a collection of data that is huge in volume, yet growing exponentially with time. It is a data with so large size and complexity that none of traditional data management tools can store it or process it efficiently. Big data is also a data but with huge size. What is Big Data? What is an Example of Big Data?

  7. Mar 11, 2024 · The definition of big data is data that contains greater variety, arriving in increasing volumes and with more velocity. This is also known as the three “Vs.” Put simply, big data is larger, more complex data sets, especially from new data sources. These data sets are so voluminous that traditional data processing software just can’t manage them.

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