The Age of Data Science

The Age of Data Science

NEED FOR DATA
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Nowadays, among all things in the developing world, one can observe the increasing demand for Data Science and Data Analytics. But why is it happening like this? Well, to unravel this mystery, let us first know why it is needed.

A Case Study :
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Let us say that a guy named ‘X’ runs a business of food. When he started his business, only a few people used to visit his shop and buy items. Later, as people found his foods really tasty, the quality of raw materials are good and fresh, his shop gets crowded more and more. Accordingly, Mr. X has to increase his stocks so that he can cater to the demands of his customers. Let us imagine now, that he expects 100 customers per day with a gross increase of 5% customers. So, he will have 5 new people coming to his shop every day along with the previous people. Well, till this much, the balance was fine. One day Mr. X’s friend decided to augment his business and expand it even further. So he had put some hoardings by the town highway. Now, hearing of his food quality and recommendations, a big bunch of customers rushes to shop at an unprecedented rate. X with a business model to accommodate some 1000 customers now faces an influx of 1 million. Obviously, this is a cause of headaches. X receives a lot of data. Also, he couldn’t keep an account of what his customers favor. This keeps him at risk of losing his valuable customers, incur losses, and also turn his soaring business into a complete mess. What could be done? The answer that might seem feasible is to manage his data. Thus we summon His highness, Data Science. 😅

The case study above is what actually happens in the market. People want to grow their business, do research, and make their company the top brand. But all this is next to impossible without the knowledge of your data.

Let us look up two important terms.
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DATA —> Data means any group of organized or scattered information or knowledge about any incident, person, object, or anything which we may define. For example, your name, address, age, etc are all data.

PROCEDURE —> These are the organized and planned sequence of steps we follow to arrange data in a meaningful order or to store them for future reference.

DATA SCIENCE —> Any systematic and practical study of data, choosing the best procedures to manage data and find out insights is called Data Science. As in Science, we study phenomena of nature, similarly in Data Science we study nature and characteristics of data.

In high school physics, most of us have learned that the Universe comprises of matter and energy. Similarly, by the definition of Data Science, we can say that the universe comprises of Data and Procedures. A planet, a star, and almost all celestial and terrestrial bodies generate data by following certain procedures. For example, the earth revolves around the sun to generate a year. A year can be treated as just a number of days, but each second of this year encounters a series of different incidents. A comet that runs past the sun, generates data about its speed, radius, latus rectum, amount of gaseous molecules dispersed in space, the amount of blue-shift, and emission of cosmic rays, etc. to account for a few. In market strategies, the rise and fall of shares, Nifty, bitcoin values, GDP, etc. affects a lot in business and must be recorded carefully.

But, a problem arises here. The problem is how can we make it helpful? Well, obviously just some random data are no better than algebraic numbers and amount to no good. So, here comes the need to organize these randomly generated data and put them to sensible use. The best way to do this is by a careful, systematic, and efficient study of this data. This can be achieved with the help of data analysis.

The Equation?
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We know the famous equation of Einstein has linked the ever conflicting duo, “mass” and “energy”. But, what is the formula to link data and procedures? Well, there is no one formula or concept but an entire series of deep statistical and mathematical ideas which bring to conclude a lot upon data. These are the analysis algorithms.

Why Data Science is the Future?
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Each and every conglomerate and MNC in today’s world experience a huge data inflow from its millions of customers online. If the data of these customers are ignored, then the business sector is most likely to miss out on important insights that could have been a game-changer for the company. But amongst tons of useful and useless information, it becomes next to impossible for a person or group of people to sort out the important and conclude something useful if they don’t follow some fixed procedure ( as it becomes for a guy to solve multiplication of 9 digit numbers in 10 seconds without the knowledge of Vedic Mathematics). Thus, data science can be the next unambiguously accepted optimum solution to this problem. So, it can be rightfully tokenized as the door to the future.

MAINAK CHAUDHURI

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