Which of the following is NOT a characteristic of big data?

Which of the following is NOT a characteristic of big data?

• A. Volume
• B. Uniformity
• C. Velocity
• D. Variety

Answer: (B)

Big data is commonly defined by several key characteristics, often referred to as the "three Vs" (and sometimes more), which include volume, velocity, and variety. Each of these characteristics highlights a different dimension of what makes data "big." Volume pertains to the massive amount of data that is generated and managed, often measured in terabytes or petabytes. Velocity refers to the speed at which data is generated and processed, emphasizing real-time processing and analytics. Variety indicates the diverse formats and types of data that are collected, ranging from structured data in databases to unstructured data such as social media posts and images. In contrast, uniformity does not fit within these defining characteristics of big data. It implies a level of consistency or homogeneity in the data, which is the opposite of what is typically encountered in big data environments. Big data is characterized by its heterogeneity, where different data types and formats coexist, requiring robust data integration and analysis techniques to make sense of the information. The richness and complexity of diverse data types are what truly defines big data, rather than any expectation of uniformity.

Big data is commonly defined by several key characteristics, often referred to as the "three Vs" (and sometimes more), which include volume, velocity, and variety. Each of these characteristics highlights a different dimension of what makes data "big."

Volume pertains to the massive amount of data that is generated and managed, often measured in terabytes or petabytes. Velocity refers to the speed at which data is generated and processed, emphasizing real-time processing and analytics. Variety indicates the diverse formats and types of data that are collected, ranging from structured data in databases to unstructured data such as social media posts and images.

In contrast, uniformity does not fit within these defining characteristics of big data. It implies a level of consistency or homogeneity in the data, which is the opposite of what is typically encountered in big data environments. Big data is characterized by its heterogeneity, where different data types and formats coexist, requiring robust data integration and analysis techniques to make sense of the information. The richness and complexity of diverse data types are what truly defines big data, rather than any expectation of uniformity.