What term refers to large or complex data sets that traditional data processing applications cannot sufficiently handle?

What term refers to large or complex data sets that traditional data processing applications cannot sufficiently handle?

• A. Big Data
• B. Data Mining
• C. Information Overload
• D. Data Analytics

Answer: (A)

The term that describes large or complex data sets that traditional data processing applications are unable to handle effectively is "Big Data." This concept encompasses the voluminous amounts of data that are generated from various sources, including social media, sensors, transactional data, and more. Due to its size, speed, and variety, Big Data cannot be efficiently managed using conventional database systems or tools. Big Data involves advanced tools and technologies designed to capture, store, manage, and analyze data at scale. Techniques such as distributed computing and parallel processing are often employed to derive insights and value from such large datasets. The other terms, such as data mining, refer to the practice of analyzing large datasets to discover patterns or relationships, rather than the data itself. Information overload describes a state where one has too much information to process effectively, potentially clouding judgment or decision-making. Data analytics is the process of examining data sets to draw conclusions about the information they contain, including trends and performance insights. While all these concepts relate to handling data, "Big Data" specifically addresses the challenges posed by very large and complex datasets.

The term that describes large or complex data sets that traditional data processing applications are unable to handle effectively is "Big Data." This concept encompasses the voluminous amounts of data that are generated from various sources, including social media, sensors, transactional data, and more. Due to its size, speed, and variety, Big Data cannot be efficiently managed using conventional database systems or tools.

Big Data involves advanced tools and technologies designed to capture, store, manage, and analyze data at scale. Techniques such as distributed computing and parallel processing are often employed to derive insights and value from such large datasets.

The other terms, such as data mining, refer to the practice of analyzing large datasets to discover patterns or relationships, rather than the data itself. Information overload describes a state where one has too much information to process effectively, potentially clouding judgment or decision-making. Data analytics is the process of examining data sets to draw conclusions about the information they contain, including trends and performance insights. While all these concepts relate to handling data, "Big Data" specifically addresses the challenges posed by very large and complex datasets.