Data science (sometimes datalogy - datalogy) is a branch of informatics that studies the problems of analyzing, processing and presenting data in digital form. Combines methods for processing data in conditions of large volumes and high levels of parallelism, statistical methods, data mining methods and artificial intelligence applications for working with data, as well as methods for designing and developing databases.


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A Beginner`s Guide to Data Science: Terms, Applications, Education, and Entry into the Profession

I think that if you find the intersection of different definitions of what is Data Science, then they will be only one word - data. All of this suggests that the breadth of Data Science is enormous. Agree, but this is not good for anyone: neither for you, nor for the business. This latitude does not provide any information about your potential activity. After all, you can do whatever you want with the data. You can build complex reports or wobble tables using SQL. You can predict taxi demand by a constant or build complex mathematical models of dynamic pricing. And you can also configure streaming data processing for high-load services operating in real time. In Ace the data science interview Nick Singh PDF book there is a perfect explanation of this.

Data Science definition

In general, where does the word "science" have to do with it? Of course, Data Science has a very serious mathematical apparatus under the hood: optimization theory, linear algebra, mathematical statistics and other areas of mathematics. But only a few are engaged in real academic work. Business does not need scientific work, but problem solving. Only giants can afford a staff of employees who will only do what to study and write scientific papers, invent new and improve the current algorithms and methods of machine learning.

Unfortunately, many experts in this field at various events often associate Data Science primarily with building models using machine learning algorithms and rarely tell the most important thing, in my opinion, where the need for a particular task arose from, how it was is formulated in "mathematical language", how it is all implemented in operation, how to conduct an honest experiment in order to correctly assess the business effect.

Who is Data Scientist?

When we realized that we didn't understand anything, it's worth talking about data scientists - data analysts.

Some believe that this position involves the construction of neural networks in Jupyter Notebook'e. Others expect such specialists to come and complete all tasks on a turnkey basis. And still others just want to have such fashionable guys on the staff. Such a different understanding of the position or misunderstanding at all can harm both you, as a candidate, and the company when hiring.