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What Is the Definition of Big Data in Hadoop Environments?
Understand the core definition of Big Data for your Hadoop certification. Learn why large-scale datasets require distributed systems rather than local servers or traditional relational databases.
Question
Which of the following best describes Big Data?
A. Only structured relational databases
B. Large-scale datasets that require distributed systems to process
C. Files stored in a single user’s personal computer
D. Small datasets managed on local servers
Answer
B. Large-scale datasets that require distributed systems to process
Explanation
Big Data is fundamentally defined by datasets so massive, complex, or rapidly changing that traditional data processing applications and single-server architectures cannot handle them effectively. It typically encompasses the “Three Vs”: Volume (size), Velocity (speed of generation), and Variety (structured, semi-structured, and unstructured data). Option B correctly identifies this need for distributed systems (like Hadoop or Spark) where data is split across clusters of computers to enable parallel processing, whereas options A, C, and D describe traditional, small-scale, or strictly structured environments that do not qualify as Big Data.