The three V's of Big Data

There is an explosive growth of data and it has changed the way that services are provided, the engagement on business, and also the association measurement of value and profitability (Krishnan, 2013). The saying “You cannot manage what you do not measure”, attributed to W. Edward Deming and Peter Drucker, explains why this digital data explosion is so meaningful (McAfee, Brynjolfsson, et al., 2012). To explain the concept of Big Data better, specialists break it down in the form of three V’s:

Data Volume is described by the amount of data that is produced continuously, and it can be different types, such as blog text, voice calls, videos files, machine logs, etc, and it come in diverse sizes, for example, kilobytes, megabytes, gigabytes, etc (Krishnan, 2013). Thinking from a social media viewpoint, as it represents a massive impact on data, since 2016, there are over 250 billion pictures and 2 trillion posts uploaded (Hansen, 2019). More data is generated across the internet in every second than were stored in the whole internet 20 years ago (McAfee, Brynjolfsson, et al., 2012).

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However, Big Data is not just huge, it is also growing very fast. For some applications, the velocity that data is generated is even more relevant than the volume. Getting data on real-time or nearly real-time gives companies competitive advantage over competitors (McAfee, Brynjolfsson, et al., 2012). An example is Facebook statistics, where 293,000 statuses are updated, 136,000 photos are uploaded and 500,000 comments are posted every minute on the platform (Hansen, 2019).

Besides big and fast, data is still extremely diverse. Variety in Big Data, is about the capacity to label the incoming data into different categories, the data can be structured or unstructured, and be generated either by humans or by machines (Whishworks, 2017).

Simplifying, due to Big Data, managers can know more about their business and directly use that knowledge to improve their decisions and performance, just because, now, they can measure it (McAfee, Brynjolfsson, et al., 2012).

References

Krishnan, K., 2013. Data warehousing in the age of big data. Newnes.

McAfee, A., Brynjolfsson, E., Davenport, T.H., Patil, D.J. and Barton, D., 2012. Big data: the management revolution. Harvard business review, 90(10), pp.60-68.

Hansen, S. (2019) ‘The 3 V’s of Big Data Analytics’, Medium. Available at: https://medium.com/hackernoon/the-3-vs-of-big-data-analytics-1afd59692adb (Accessed: 05 Fev 202­­0).

‘Understanding the 3 Vs of Big Data - Volume, Velocity and Variety’ (2017) Whishworks. Available at: https://www.whishworks.com/blog/big-data/understanding-the-3-vs-of-big-data-volume-velocity-and-variety (Accessed: 06 Fev 2020).