#onlinedating | A Brief Insight into the Era of Big Data Analytics | #bumble | #tinder | #pof

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.

Therefore, through the use of Artificial intelligence techniques like natural- natural-language processing, pattern recognition, and machine learning algorithms, on devices, sensors linked with the Internet of Things, we can now reap immense benefits of Big Data over numerous fields. While this amps up the speed of construing massive quantities of data, and enables instantaneous decision making, it further helps in innovation and designing better tools and software for deeper probe and other requirements. These comprise finding a suitable drug in the pharmaceutical industry, checking which hotel fits our budget, on what factors a firm becomes a market leader, predicting weather and twitter trends, better song recommendations based on your playlists, and so on. The potentials and possibilities are limitless!

According to a New York Times article, retailers, like Walmart and Kohl’s, analyze sales, pricing, and economic, demographic, and weather data to tailor product selections at particular stores and determine the timing of price markdowns. Shipping companies, like U.P.S., mine data on truck delivery times and traffic patterns to fine-tune routing. Online dating services, like Match.com, constantly sift through their Web listings of personal characteristics, reactions, and communications to improve the algorithms for matching men and women on dates. Police departments across the country, led by New York’s, use computerized mapping and analysis of variables like historical arrest patterns, paydays, sporting events, rainfall, and holidays to try to predict likely crime “hot spots” and deploy officers there in advance.

According to Analytics Insight report,” Reinventing Business with Disruptive Technology” the global market of Big Data is forecast to grow at a CAGR of 10.9% from US$179.6 billion in 2019 to US$301.5 billion in 2023.

Today, Big Data is employed to find a cure for COVID-19, study the pandemic hotspots, previous airlines route, and based on the data, forecast the epicenters of next pandemic waves. It is also being used to analyze the impact of COVID-19 on businesses, supply chain distribution routes, stock market, and job sectors, and analyze models that can help revive the global market.

So, it is safe to assume that as the days pass by, with increasing data pools, complexities and boom of industry-oriented necessities, Big Data is here to cater to these needs in a long, long run. Especially, when paired with and powered by other technologies like IoT and Artificial Intelligence, it is here to stay and guide us to the next-generation innovative, digitally transformative world.

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