Which of the following is a key difference between Big Data and Traditional Data?

Big Data is defined by the 4 V’s : Volume (huge amounts of data), Variety (different types of data such as text, images, videos), Velocity (fast rate at which data is generated), and Veracity (uncertainty or trustworthiness of data). These attributes differentiate Big Data from traditional data, which typically involves structured data, slower data processing, and is less complex in terms of data variety. Why Other Options Are Wrong : A) Incorrect : Big Data often requires specialized NoSQL databases or distributed storage solutions like Hadoop or cloud services. Traditional relational databases like SQL are not suitable for the scale and complexity of Big Data. B) Incorrect : Traditional data systems are usually structured and are not optimized for handling unstructured data such as text, images, or videos, which are the hallmark of Big Data. D) Incorrect : Traditional data systems generally process data in batch mode, not in real-time. Big Data systems, on the other hand, often involve real-time data processing. E) Incorrect : Big Data systems are highly scalable and designed to handle very large datasets by distributing the processing across multiple servers or nodes, whereas traditional data systems often struggle with large-scale data processing.