Which of the following characteristics best differentiates Big Data from Traditional Data ?

Explanation: Big Data refers to large, complex datasets characterized by the 3Vs —volume (sheer size of data), velocity (speed of data generation and processing), and variety (structured, unstructured, and semi-structured formats). Traditional Data, on the other hand, is smaller in scale, structured, and typically managed using relational databases like SQL. Big Data technologies (e.g., Hadoop, Spark) handle vast datasets, enabling advanced analytics such as machine learning and real-time processing, whereas Traditional Data is used for routine business operations and small-scale analytics. Understanding these differences is critical for selecting appropriate tools and techniques for data analysis. Option A: Both SQL and NoSQL databases can handle traditional and Big Data, depending on use cases. Option C: Big Data often requires significant preprocessing and cleaning due to its complexity. Option D: Both can be used for predictive and real-time analytics; it depends on the tools and methods used. Option E: Big Data can be stored on physical servers; distributed systems are used for scalability.