20 | Big Data Simplied
2.1 INTRODUCTION
There is a plethora of market forces that are driving the paradigm shift in modern data management.
The factors that play a main role in modern data management are briey explained as follows.
• Data explosion: In today’s world, there is a massive outburst in the volume of data being
generated by machines, mobile devices and social media interactions. According to an IDC
whitepaper dated on November 2018, by 2025, 175 zettabytes of data (1 zettabyte is 10
raised to the power of 21 number of bytes or
10 byte
s
21
) will be generated and according to
a study published by Intel, there will be 200 billion connected devices by 2020.
• Affordable technology: Traditionally, organizations have adopted a human-led approach
towards data discovery, data quality management and data governance. This trend is now
changing into a machine-led approach towards data management, thanks to technologies like
Artificial Intelligence (AI), Blockchain, etc. Again, while traditionally, data has been managed
in on-premise data centres, it is predicted by an IDC whitepaper dated November 2018 that
by 2025, 49% of the world’s stored data will be on public cloud. Potentially, by 2020, there
will be more than 6 billion smartphone users globally, as reported in a study published by
Statista. Likewise, the average cost of a sensor device will decline from $1.30 in 2004 to an
expected $0.38 in 2020, as reported in a study by The Atlas.
• Change in expectations: Traditionally, enterprises have been leveraging data to analyse
historical performance and to improve operational efficiencies based on past experiences.
However, the focus has now shifted to leveraging data for deriving predictive actionable
business insights. Data is now considered as an asset that can be used as a competitive differ-
entiator in the market.
2.2 THE TRANSITION TO BIG DATA
When a business becomes more mature, it needs to deal with more complex data sets and lev-
erage that data to earn higher prots, improve productivity and improve customer experiences.
It will be helpful to understand this evolution with the example of an online retail store.
In its most rudimentary form, a website of the store contains the following features.
• A product catalogue with visual content, such as views of the products from different angles.
• Ability to drill down to product details and product hierarchies.
• Ability to place an order for one or more products online.
• Maintain a basic buyer profile by asking the customer to register herself.
• Store the profile information of the customer, such as his/her name, address, phone number,
e-mail address, etc.
These are essentially static information, that can be refreshed periodically, as product features
change, or new products are introduced, or buyer information such as address changes. However,
information pertaining to sales are captured more frequently, as and when sales happen. All of
these are structured data.
M02 Big Data Simplified XXXX 01.indd 20 5/10/2019 9:56:51 AM
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