In this age of information technology, data scientist and business analytics are two popular names. Because now data means something huge. Big companies want data first to take their business forward. Many big businesses can avoid losses if a data analyst comes up with the right data in a timely manner and comes up with a new idea.
Let’s make it easy. Suppose a new company decides to bring its own toothpaste to market. The owner wants the customer to accept it. For this you need to do market research first. Which is called market research. Research needs to be run on users. It will be seen which people use which toothpaste more, why they do it, what is the reason why they are buying which toothpaste year after year etc. All this is data. And if you know this information, the company will be able to understand exactly which toothpaste the customer will grab if he brings it.
It is the job of the data scientist to sort out the information and determine the future course of action.
In fact, in the last five years, 90 percent of businesses have focused on business data. According to recent LinkedIn data, the job market for data science specialists is growing rapidly. The names of the posts are more or less the same – Data Scientist, Data Science Specialist, Data Management Analyst etc. According to the data, the demand for these positions in the job market has increased by 46 percent since 2019.
More about data science
Suppose again, you entered a book sales website. There he searched by writing the names of his favorite books. After a while, it was seen that the advertisement of that website has started appearing on your Facebook homepage and it is also showing the advertisement related to the books you have searched for. How did this happen? Here, too, is the data scientist’s buzz.
Your interests are collected in the form of information (data). It is analyzed in the software and the product of your potential choice is presented to you. The advantage of the trader is that he is able to deliver the advertisement to the potential customer of his product at low cost and time. Another name for this work is data analysis.
Data analysis and data analytics one?
Even if you hear one thing, the work is different. Suppose a clothing store started keeping buyer information. The job of the person who will do the data analysis of the store is to determine the nature of the buyer from the sales account. For example, how many times a month you come there, exactly what day of the week you come, what kind of clothes you buy, how much you buy for, how old you are, what color you like around, etc.
From here, the analyst can create many types of charts. It will be seen later that you will come to more stores if you are offered exactly what kind of offer.
Basically, those who do data analysis work with information from the past. And with that, he created a possible scenario for the future. This gives a complete picture of the business. Weaknesses can also be easily identified.
Now let’s move on to data analytics. The task at this stage is to determine the future. Suppose, the reasons for the decrease in sales in a store will be found out. Experts in data analytics will come up with the formula to determine what needs to be done to increase sales on this date.
What to do to learn data science?
I want to have knowledge of mathematics. It is not a matter of learning all the complex formulas and equations in a textbook. Must have a clear idea of elementary mathematics.
Second, it is important to be proficient in statistics. A clear knowledge of all the formulas and methods in probability, sampling, different types of averages, and different formats will take you many steps forward.
Remember, these are the initial preparations. If you want to be a good data scientist, you must be proficient in all aspects of statistics. Because the job of statistics is with data.
Third, learn the Python programming language. Python teaches you how to do data analysis through coding. The same thing can be done in ‘R’ language without Python. However, knowing Python is an additional qualification to keep up with Artificial Intelligence aka Artificial Intelligence.
How to learn?
You will find numerous tutorials on YouTube. There are also many training centers. There are many free platforms online where it is possible to learn data science just like in class. Remember, training will tell you the method. You have to take the main lesson yourself. Creating problems on your own, finding alternative ways to solve them, you have to practice these regularly.
Data analysis is not an object to be learned in an hour sitting day by day. You have to decide with patience. The focus must be fixed first. You have to figure out exactly what you want to learn. Then he plans accordingly. It is better to learn programming as well as mathematics.
Remember, a programming language is just a computer language – not a lot of memorization like medicine or chemistry. Patience is essential to become proficient in this language. Established data scientists say they want to practice at least one hour a day to learn the programming language needed for data science.