Data Science Definition – The Smart Beginners Guide

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Data Science" has become a trendy concept, often used wrongly to describe just about anything and everything. It is often thought that Data Science is inseparable from Big Data, that Data Science is the art and manner of analyzing enormous volumes of data. This is largely inaccurate. The question of volume is secondary. Another mistake often made is to systematically associate Data Science and Machine Learning. We did not wait for Machine Learning to do mathematical and statistical modeling. These are all the confusions that we will try to clear up in the following paragraphs.

Before we begin, a little semantic reminder. In Data Science, it will have escaped no one, there is "Science". Data Science is indeed based on scientific methods , on mathematical and statistical knowledge, and not only on empiricism and intuition. In Data Science, there is also Data, that is to say "data". On this point, it is important to understand that "data" and "information" are not synonymous. Data are raw and unorganized elements that need to be processed to acquire meaning. Data, unprocessed, left to its chaos, is useless. "Information" is data that is organized, processed, structured and carries meaning. The whole art of the Data Scientist is to transform raw data into information that can be used by the company.

With these few remarks and clarifications made, we can begin to try to uncover paraguay whatsapp list the secrets of this new discipline, which is clearly fascinating and has a bright future.

Summary

Since when have we been talking about Data Science? And why?
The fundamentals for understanding what Data Science is [Definition]
The life cycle of a Data Science project
Practical case: prevention of diabetes
Summary

Since when have we been talking about Data Science? And why?
Just 5 or 6 years ago, almost no one knew about this discipline and those who did know about it did not always take it very seriously. As the graph below shows (thanks Google Trends ), the use of the terms "Data Science" and "Data Scientist" really took off in 2012. In fact, we talk about "Data Science" much more often than "Data Scientist".

google trends data science

The second observation is that despite everything, we were talking about Data Science before 2008, and even in 2004 (unfortunately, it is not possible via Trends to go back before 2004...)! So, those who tell you that Data Science is a very recent discipline are wrong. Data Science is an older discipline than we think. In a sense, this discipline has always existed. Except that 30 years ago, we did not talk about "Data Science", the term did not exist.