By: Mahesh H Nayak, Chief Operating Officer, SAP Labs India
A few years ago, data analytics was just a simple term as it meant making sense from data
stored in columns and rows in a database. However, with the evolution of the Internet
and the expansion of its reach and utility, data has become ubiquitous and comes in varied forms and shapes. Thus, data storage in a structured manner is no longer valid. With the data becoming pervasive and diverse, a new challenge emerged—that of making meaningful sense out of it so as to derive intelligence at rapid speeds all in the
hope of gaining better decision making powers and insights. In the new world we live in, the boundaries are becoming more virtual and we are moving rapidly towards a connected
world, where the boundaries of personal life are inseparable from the tasks we do for a living. Everything, from the mobile phones to our homes, is connected.
The large volume of data that sensors, machines, smart devices, network grids among several others are ejecting is driving the concepts of ‘Internet of Things’ or ‘Industry 4.0’, fuelling big data. We possibly are on the verge of the next big industrial revolution. Just imagine the number of jobs it could create in our developing economy. In the past decade, several engineering and manufacturing companies invested heavily in technology in anticipation of gaining intelligence that would help them unlock the secret to the future investments they could make. Their systems however failed to give those insights. Today, technology provides us the speed and capabilities like predictive analytics to simulate actions and decisions on data that has been collected over the years, giving us renewed confidence to take actions.
THE CORE FACTORS
The new world around big data can be defined by four core parameters—speed at which the data can be analyzed; confidence in the analyzed data; variety of analysis that can be done; and ease of availability of this analysis to consumers over different devices for easy consumption. A few other factors also play a significant role to ensure that the big data concepts become easily accessible. These include availability of large data store at significantly low costs, the advent of in-memory computing, and the rapid shrinking of hardware costs. To leverage the power of big data and for this phenomenon
to strive further, we will need to significantly change our business models, processes that run an enterprise— the ultimate goal is to move into a data-driven decision making process.
We need to move from a human intelligence and intuition-driven model to a model where human intelligence combines with machine intelligence. Just imagine a world benefitting from this model—like for example, a world where medication could reach before the onset of an epidemic or how an intelligent supply chain and manufacturing firm can produce goods based on customer behavior, buying trends and make it available instantly or a scenario where all the vital devices and equipment we use in our daily lives become fail-proof due to self-healing made possible by their predictive capabilities.
Today, all of this is possible and beginning to happen around us. The challenge now is to make it a common practice or knowledge rather than it being adopted by a
CHALLENGING THE TRADITIONAL MODE OF BUSINESS
Big data also provides opportunity for start-ups to come up with new business models that challenge the traditional mode of doing business. Recently, a few start-ups in the big data space I was interacting with showed me some interesting technology use cases. Like for example, a company using Drones to collect visuals and images for analysis for varied purpose like security and crop insurance.
All of these use cases in the past depended heavily on human intelligence and intervention. Today, it is being made possible by collaboration between man and machine
which definitely is a smarter way to do things. Like in all domains, science needs experts or human intervention to decipher the intelligence that comes out from the wonderful tools and the machines that collect them. We will need to avoid the urge to outsource all decisions to a box of algorithms but depend on it for providing us with assessments and insights that are hereto unknown. In a real world unless we understand these rules clearly, it is hard to do away with the biases that come built in.
BIG DATA IS HERE TO STAY
Despite the visible benefits of harnessing and utilizing big data, several sceptics view it as a myth or a hype, with some of them predicting a big data bubble burst, similar
to the dotcom bubble burst.
Irrespective of what big data will be described as, it is here to stay in the enterprise and will continue to grow at an exponential speed. The dotcom bubble burst did not signal the end of Internet. Therefore, the sooner we adopt and embrace big data, the faster would be our gains.
(The views expressed in this article are those of the author and may not reflect those of SAP Labs India)
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