If I give you the data of Latitude Long Route of all the people of India and tell you people which shop is on which latitude long duty? Which mall is which person's house? Now looking at that data, you guys tell me such things that 30% of the people come out of their house on Sundays. To eat food and 10% of the people who are there, go out on Wednesdays. 20% of the people go out to eat outside the house. To eat and drink fried rice to enjoy outside, you gave me some insights from that roti that I had data from a latitude nine u.
What Is Data Science?
With that number only, you converted those numbers into meaning and the same thing happens. What tool would you guys use for a beta scientist to convert beta into meaningful insights? Doesn't matter at all. You are such a list, Insight Steve, from that data, URT Scientist Edison is also becoming a Data Scientist, such a career is becoming a very good option, but if people talk now. Today, 2025 years ago, when the Internet just came, the data started collected with us. What happened then was that the data that was there, we used to see people in very small mode.
If we got the data of employees of any company, then we used to manage that data in the same way as excel. A person was able to extract insights just by looking at it with his eyes and it did not take much effort to convert any Big Data use invalid data into these sites because at that time the usage meant only 200 300 data per day. Today, if we talk about people, then we have Millions Williams, TV Brilliance and everyday audio top rises. I have so much data that 20 minutes of a human being, what if a person sat down for the rest of his life? He would still be given his whole life to read, but if insights would not come out of the data, then it used to be like this in MI3 Nineties.
The Internet had just shown its presence. There were many who were high class and knew technology very closely. Just say you were on the internet. A little beta who does not find something called a smartphone was given, which as time progressed. We got YouTube in 2005. Facebook came in 2000, followed by Instagram. We had Snapchat come to us and this kind of application made people come on the internet for what it is. People became addicted to it and we got so much data. There was so much data that we liked that man now a person needs to extract insight from these data through the dedicated lead computer so that he can restore the business so that some good decisions can be made from that meaningful insight.
Time went on like this. By the way, our machine, the amount of our computer, the amount of dopamine, two computers, three amounts of storage cards, the way we are approaching things, you from a technology standpoint, that machine is getting very much improved. Powerful making and beta size Today when the doors of career opportunities are opening up for people, what is a Data Scientist. If I give a very simple answer to this, then there is a world of Data Scientist who converts beta into Insight and converts data into Meaningful Insight so that anyone can make good decisions by seeing a 3D man and making a Latitude Launch Nucleic Sample.
If any person is able to speak this or whether thirty percent people eat out on Sundays, then what they have on Sundays, they can increase the IT of their shop or their nation. Can hire as many employees as possible. To serve the people only for that day and by doing so everyone can benefit. Most of the other T entities as of today are related to the data that has been collected. Today, all of you are leaving a footprint on the Internet because of people leaving a footprint on the Internet.
Many such people generate as many times as they interact with the computer from the Internet from their phone and who are the most of that data is collected till now and after storing it is given to the data scientist so that those people can get insight. and benefit the companies. With the help of that data, now data collection is also a very important job of a data scientist, which is data, it involves collecting, beta lining, beta lining, building borders, and crisis data, so all these three jobs are very important. The machine learning that happens also comes within the data size. Just the difference between Data Scientist and Machine Learning Engineer Geotech focuses on the Machine Learning Engineer who is a Machine Learning Algorithm while the one who is a Data Scientist will be over and who will be the pipeline of D. Where is it getting collected and how to get it analyzed.
আজকের আইটির নীতিমালা মেনে কমেন্ট করুন। প্রতিটি কমেন্ট রিভিউ করা হয়।
comment url