analyse and systematically extract information from datasets that are too large or complex to be processed by traditional data processing techniques.

A white paper by International Data Corporation (IDC) reports that the global data volume has grown
exponentially from 4.4 zettabytes to 44 zettabytes between 2013 and 2020. It also predicts that the volume
of data will reach 175 zettabytes by 2025. Zettabyte is a unit that is used to describe the amount of data,
and 1 zettabyte equals 1021 bytes (that is, 1,000,000,000,000,000,000,000 bytes!). The world has
officially entered zettabyte era and data is still being generated at a staggering speed. For example, in
retail Walmart processes more than 1 million customer transactions every hour; in tech, Facebook users
upload more than 350 million photos every day. With such an amount of data and the speed at which
data is being generated, comes the desire to analyse and extract information from the datasets. Often the
information that is extracted from a big dataset as a whole is much more useful than the collection of
information extracted from small individual datasets. This desire gives rise to big data, which, as a field,
studies the techniques that analyse and systematically extract information from datasets that are too large
or complex to be processed by traditional data processing techniques.

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