Synopsis: Big data is a relative term describing a situation where the volume, velocity and variety of data exceed an organization’s storage or compute capacity for accurate and timely decision making. Big data is not a single technology but a combination of old and new technologies that helps companies gain actionable insight. Therefore, big data is the capability to manage a huge volume of disparate data, at the right speed, and within the right time frame to allow real-time analysis and reaction. As we note earlier in this chapter, big data is typically broken down by three characteristics:
– Volume: How much data
– Velocity: How fast that data is processed
– Variety: The various types of data.
Although it’s convenient to simplify big data into the three Vs, it can be misleading and overly simplistic. For example, you may be managing a relatively small amount of very disparate, complex data or you may be processing a huge volume of very simple data. That simple data may be all structured or all unstructured. Even more important is the fourth V:veracity. How accurate is that data in predicting business value? Do the results of a big data analysis actually make sense? Determining relevant data is key to delivering value from massive amounts of data. However, big data is defined less by volume – which is a constantly moving target – than by its ever-increasing variety, velocity, variability and complexity .
Published: November 2014 | ISBN: 978-1503063716
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