The evolution of Big Data and its implications

15-05-2015
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The scope of Big Data in the world of Analytics is growing and changing dramatically, constantly evolving to redefine its self every day. Considering the amount of data generated to how they have been structured, Big Data offers enormous challenges and the biggest business opportunities for enterprises today.

With more and more businesses robustly switching from analog ecosystem to digital, both individuals and corporates are generating such large pools of information that experts predict there would around 4300% leap in the annual production of data by 2020. Most of this data will be in the cloud ; In other words, by 2020 about a third of all data will pass through the cloud.

The epic rise of unstructured data like photos, videos and social media has fostered a new breed of non-relational databases, allowing them to unveil their own structures, patterns and trends. The migration from merely collecting data to connecting it, has aided businesses to better draw inferences and relationships between datasets, leveraging actionable insights for better enterprise decision making.

The number of industries gearing themselves to accommodate the Big Data practice is on an exponential rise. Whether it is comparing utility meteorological data to spot trends and efficiencies or considering ambulance GPS information with the records of the hospital to identify correlation between response time and survival or hanging a tiny device around your neck that tracks your movement, calories and sleep to get you back on line with your personal wellness, they are all reincarnations of Big Data.

Although it’s difficult to point out a singular reason for the creation of Big Data revolution, it would be fair to say that an array of factors would have developed and caused the phenomenon of Big Data as we know it today. It can be anything from the increasing amount of digital data at disposal to inexpensive data storage options to advanced computers which help with better business analytics that would have pushed Big Data to where it is today.

That being said, having such huge amounts of data with volume, variety and velocity data at ones disposal also means it becomes equally or more challenging for enterprises to draw relevant Actionable insights and Business Intelligence (BI) to make better business decision making. Storing, searching, comparing, combining, visualizing and refining the data can be big challenges. Another challenge putting Big Data to use is getting your hands on the right information. Some IT companies like Microsoft works with Hadoop – an open source data platform which helps efficiently manage unstructured data to work around these challenges.

The implications and effects of Big Data spans across different industries. unlocking its infinite potential depends cutting edge enterprise datacenters are and how advanced their analytics practices are. A hospital may use a critical gene sequencing to prevent the outbreak of an antibiotic resistant bacteria, or a university may identify dropping activity levels of a student in lines with drop-out rates, reaching out to assist, or a rail-road enterprise may get a notification from a sensor saying that a preventive fix is on demand, saving cost and time taken to remove the trains from the tracks.

In summary, Big Data makes its essentially personal for all of us, residents of this era. It can make smarter cities, greater academic learning, faster medical breakthroughs and more efficient use of enterprise resources. The future of Big Data looks bright. McKinsey reckons that over a million of Big Data related jobs would open up in the next couple of years. However in order to realize this potential it would be essential that the tight combination of technology, skillsets, processes, planning and industry application understanding is used to harness and use Big Data to it’s fullest potential.



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