3 steps to maximize big data harvesting and refining yields

Too much data that is harvested goes to waste. Here are simple ways to get the most from your big data refining and harvesting efforts.

In the big data context, data harvesting can have different definitions and applications. Some practitioners define it as scraping off data from a variety of web-based sources for the purposes of data aggregation and analysis; in other cases, an organization harvests its internal data, which is drawn from various systems.

Author: Mary Shacklett


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