Final answer:
The term Big Data is best defined as option 2) large and complex data sources that defy easy management with traditional data processing methods.
Step-by-step explanation:
Big Data encompasses vast volumes of data that cannot be effectively processed, managed or analyzed with conventional data-processing techniques. It is often characterized by the three Vs: volume, velocity, and variety.
The vast amount of data—from petabytes to exabytes—is too large for traditional databases to handle. Velocity refers to the speed at which data is being created, collected and processed. Lastly, variety indicates the range of data types and sources.
For example, the Sloan Digital Sky Survey (SDSS) generated data at a rate of 8 megabytes per second, leading to a total of over 15 terabytes over the course of the project, requiring advanced computer algorithms and supercomputers for processing.
Such tasks become even more challenging when the data is not just vast but also complex, such as differentiating subtle variations in spiral galaxies for the Galaxy Zoo project. This complexity is why Big Data often requires new forms of processing to enable enhanced decision making, insight discovery, and process optimization.