Big data is an all-inclusive term used to describe vast amounts of information. In contrast to traditional structured data which is typically stored in a relational database, big data varies in terms of volume, velocity, and variety. Big data is characteristically generated in large volumes – on the order of terabytes or exabytes of data (starts with 1 and has 18 zeros after it, or 1 million terabytes) per individual data set. Big data is also generated with high velocity – it is collected at frequent intervals – which makes it difficult to analyze (though analyzing it rapidly makes it more valuable). Additionally, big data is usually not nicely packaged in a spreadsheet or even a multidimensional database and often includes unstructured, qualitative information as well. One of the most important distinctions between big data and large data is the speed at which the data must be captured and available for analysis. Big data has urgency and requires real time or near-real time information delivery.
Big data is often of a few varieties: social media data, machine data, and transactional data. To learn more about these types of data, check out our Big Data FAQs.
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