One common misconception among people about data science is that it is all about a single discipline. But the actual fact is that it is a blend of the various disciplines which are interconnected. Hence, it is interdisciplinary.
It is the science of using various scientific techniques to extract useful data in various forms from a large pool of information. Speaking of forms of data, the data may be structured or unstructured. This process is called data mining.
Is Data Science Worth The Hype?
Why not? According to Harvard Business Review of 2012, Data Science has been called the sexiest job anyone could get in the twenty first century. It has developed a lot in the recent years and there have been a significant increase in the number of jobs and vacancies in various local firms and multinational families due to the current increasing demand in data science in the information technology sector.
How is Data Science Related to Statistics?
It has not only brought a boon in the sector of information technology, but has also influenced the business sector to a large extent. There has been a noticeable rise in the job openings in the business sector as well. It is very closely linked to statistics. In fact, some data scientists have asserted that there is no difference between it and business statistics. According to them, they are the same. But, apart from that, there are some critics who have tried to belie the aforementioned assertion by stating that data science is just a redundant term that has arisen out of business analytics itself. But, the bottom line is that both data science and business analytics employ various scientific and non scientific techniques. Both of the things include using various scientific and non scientific methods to extract out and analyze data and use it in various contexts. Hence, it can be safely concluded that they are indeed very closely linked to one another.
Machine learning is a very important aspect. Making a machine learn is something which comes from feeding the machine with data only. Hence, there are various aspects, but it is the data scientist who has to decide where his or her interest lies and where he or she should specialize. Machine learning is a very vast topic, yet it is just a fraction of data science. This can give one a clear idea as to how wide and vast the field of data science is. Also, machine learning is also divided into various subparts like artificial intelligence, also abbreviated as AI. It gives a computer an ability to communicate with the user and hence do the necessary task. One needs to be good at programming to be a good data scientist. For machine learning, programming in python is preferred mainly. But it is totally up to the user as to which programming language he or she wants to code in.
Comments are closed.