A common misconception about data science is that it involves only one discipline. But the reality is that it is a mixture of various interrelated discriminations. Here it is interdisciplinary.
It is a science to extract various forms of useful data from a large amount of information using various scientific techniques. When it comes to data forms, data can be structured or unstructured. This process is called data mining.
Is data science worthy of hype?
why not? According to the 2012 Harvard Business Review, data science is known as the sexiest job anyone can get in the 21st century. It has grown rapidly in recent years, as the current demand for data science in the information technology sector continues to increase, and the number of jobs and vacancies in various local and multinational households has increased significantly.
How is data science related to statistics?
It not only brings good news to the field of information technology, but also affects the business sector to a large extent. Job vacancies in the business sector have also increased significantly. It is closely related to statistics. In fact, some data scientists assert that there is no difference between it and commercial statistics. According to them, they are the same. But beyond that, there are some critics who try to believe the assertions by declaring that data science is just a redundant term generated by the business analysis itself. But most importantly, data science and business analysis use a variety of scientific and non-scientific technologies. Both of these aspects involve the use of various scientific and non-scientific methods to extract and analyze data and use it in a variety of environments. Here, it is safe to conclude that they are indeed closely connected to each other.
Machine learning
Machine learning is a very important aspect. Making machine learning means powering the machine only through data. There are various aspects here, but the data scientist must decide where his or her interests are and where he or she should focus. Machine learning is a very broad topic, but it is only a small part of data science. This gives a clear understanding of the breadth and breadth of data science. In addition, machine learning is also divided into various sub-parts, such as artificial intelligence, also referred to as AI. It gives the computer the ability to communicate with the user to perform the necessary tasks. People need to be good at programming to become good data scientists. For machine learning, the main choice is python programming. But it is up to the user to decide which programming language he or she wants to write.
Orignal From: Data Science - Nature and Influence
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