Below are some of the characteristics of Big Data, except ...

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Starting with a broad view of Big Data, the core ideas revolve around handling large, diverse, and fast-moving datasets with distributed processing.
Option A: 'Data exist in different types and formats' is indeed a hallmark of Big Data. The variety (types and formats) is a key characteristic that motivates the use of flexible storage and processing frameworks.
Option B: 'The volume of the data is so Big that they must be stored in a Data Warehouse' sounds plausible at first glance, but it is not a defining trait. Big Data often requires scalable storage and processing that goes beyond traditional data warehouses, sometimes using data lakes or distributed file systems. The requirement to store in a Data Warehouse is not a universal or necessary condition, and mischaracterizes the typical architecture.
Option C: 'Data are being generated rapidly in real time' aligns with the velocity aspect of Big Data. Real-time or near-real-time data generation is a common scenario that drives streaming analytics and fast ingestion pipelines.
Option D: 'Usually necessitate highly distributed data processing' captures the practical reality of Big Data workloads. Large-scale datasets typically require distributed frameworks (like Hadoop, Spark) to process efficiently across many machines.
In summary, while A, C, and D describe commonly observed aspects of Big Data (variety, velocity, and distributed processing), option B asserts a storage medium requirement (Data Warehouse) that is not a fundamental or universal characteristic of Big Data environments; it is more about architectural choices and not an intrinsic property of Big Data itself.

COS10022 Lecture 1_Knowledge Check

Below are some of the characteristics of Big Data, except ...

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