Is Data Science New…?

Data Science, now a days a most common word on the lips of almost all tech professionals. In country like India, the popularity for this word has tremendously increased because of massive use of internet facilities. After the launch of free internet data services, the use of internet has increased manifold. The data generated from e-commerce businesses, social networking sites, YouTube, IOT devices etc. is huge with great variety and velocity. To deal with these huge data and to know about the story behind it, data science has become the most popular among businesses for the last 6 to 8 years. In recent days, Data science is applicable in any domain like, internet search, social networking sites, entertainment industry, health care sector, internet shopping, finance, marketing, weather forecasting etc. But the question is whether this technology is new or it also existed before the era of internet. Yes, data science was there but none of us were aware of it. This is explained with the following examples :-

1. A fruit seller sells Mangoes every year during summer. At the starting of the season , in April he keeps the price of mangoes high as less quantities of mangoes are available in the market. The customers in turn are not willing to buy mangoes at such higher price, so he keeps less stocks in his shop. Again in the month of May, a lot of Mangoes are available in each and every shop, so the price is lower. Customers want to buy mangoes frequently and in large quantity. But if there is any festival during that season, the demand for mangoes or other fruits is much higher so as the price. Thus, the fruit seller always has a rough intuition about his sales depending on his experience(previous data) and accordingly he fills stocks in his shop. Here he does not require any data science for predicting and analyzing sales.
2. In a grocery shop, maggi noodles and sauce, rice and daal, oil and spices, potatoes and onions are always kept together in the front rack, so that those items are easily available for the customers. The reason behind this strategy is the demand for these items which are often bought together by the customers. In this scenario, the shopkeeper does not use any Machine Learning algorithms to generate Association Rule.
3. In olden days, my grand mother’s generation could easily forecast whether the day will be sunny or rainy after waking up in the early morning. They never used to follow any weather reports. By just observing the sun’s position in the sky they were able to predict the weather of that particular day.
4. Once my mentor said that the Pakoda sale increases during rainy days as compared to other days. As people prefer to eat Pakoda specially in rainy days, so Pakodawala knows if it rains then his sales on that day increases, thus he prepares more. Although there is no cause and effect relation between rain and Pakoda but still it is based on the preference. This is one of the analysis done without any statistical science.

The above examples are very simple to understand the existence of data science. But because of 3 V’s( Volume, Variety, Velocity )of data, getting insights from data seems to be very complex and important as well for attracting customers. Therefore, the advancement in data science with statistical proofs has become necessary for taking right business decisions.

Hello! Everyone, this is my first blog and I accept your valuable comments so that I can improve my skills and thought process and write something better.