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BIG DATA ANALYTICS- Data is growing, expanding, and can sometimes be overwhelming. But if you are obsessed with data and numbers, then maybe you are born for the career of data analyst or data scientist. You can help businesses make sense of the data amassed from various sources and in multiple formats — unstructured, scattered, structured— to draw actionable insights, make piloted decisions, cut costs, and lift sales. This data can be from Web traffic and social network comments, as well as software and sensors that monitor shipments, suppliers, and customers, research or survey data.

Therefore, to harness the floods of data, countries will not only need more hiring in data analytics but also train the existing workforce for efficient mining and analysis of the data. They need to understand that data not only impacts businesses, but also industries like healthcare, sports, research, e-commerce, advertising, and previously thought unlikely areas like politics, climate change too as they evolve into data-intensive areas. This drift can shape how we arrive at decisions and discover new insights. What was a marquee topic at the beginning of the century is now a buzzing dashboard that can a) set one’s company apart from rivals and b) speed up the decision-action process.

This leads to the birth of Big data which refers to the emerging trend of disruptive modern technology for a new approach to understanding the world and making decisions. Due to a sudden rise in usage of devices and sensors in household gadgets, automobiles, industrial machines, surveillance, and automated devices, there was also an upsurge in linking them with artificial intelligence and standard computer through what is now termed as Internet of Things (IoT). Hence data now started appearing in new streams piling up on the existing ones. While computers can process data in the form of words, images, and videos, it does take an enormous amount of time for the same. Sometimes the results may not be what the users expect. Not only that, but it so happens that most of the data is rendered unprocessed. At the same time, firms spend huge amounts of money, extra storage spaces, and other resources of them without any fruitful results or being accessible by other departments or platforms.

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Article Credit: Analytics Insight