Introduction to Data Science Skills

Data Science, ah such a beautiful profession in the words and deeds of those who love to do the job! As an important point to every job, love for the profession is essential. To love the job, one should have the necessary skills to do the same, whether inbuilt or acquired. We have seen many business people who acquire the business from their family and build it into an empire. And other business strata, who prepare themselves to face the worst, acquire the skills and become the best in the slot. Now, let’s see data science skills.

Following are the Types of Data Science Skills:

How many of us have hated mathematics as a subject during our school days? Almost all of us are right. Here I am going to tell you a heartbreaking revelation. Mathematics is very much important for data science, be it statistics, probability or algebra or whatever. Statistics show us that the data which we collected has a pattern or not. It makes us say that there should be a mean and variation for every data. Probability shows us the future of data, whether it is going to happen or not. Also, it says about the past as well.

Gone are the days where statisticians worked with pen and paper or with a calculator to analyze a company’s sales or benchmark the competitor company’s sales. Now we could do all these things with programming, not all these but more than these. We could see how far the data takes us in the long run, whether the data was consistent in the past and how we are doing in the present.

When we read the newspaper, we skim and skip the most important news, but we read mostly sketches. It is a human notion to see anything and to be registered about the same in mind. So is visualization skill indispensable in Data science? I would answer it with a big Yes. The entire data of maybe 100 pages can be minimized to two or three graphs or plots. Don’t you feel it be cool? I feel so.

It is paramount to convey our findings either to a group of teammates or senior management. Communication helps us to reach a level higher than what we really fight for. Being a good communicator helps us share our ideas and to find discrepancies, if any, in the data. Presentation skill is most important in a project to showcase data findings and plan the future. Looking at each other’s eyes to convey a message is important during the presentation.

So did I miss any skill to be acquired so that you can be in the field of data science? Analytical skills are equally important though I haven’t stressed it because mathematics covers all those hot topics. Curiosity about data and leadership skills to make the team work together makes you great in data science. I want to conclude this writing by saying that no skills are underrated. And all the skills can be acquired to become a professional data scientist. Hard work to focus on what you are doing; a little patience to do data cleaning is not to be avoided in the long run.

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