Recently, the consumption and innovation of information technology in the world has surged. Everyone, from a child to an 80-year-old man, uses the facilities that technology provides for us. At the same time, population growth has also played an important role in the tremendous growth of information technology. Now, with hundreds of millions of people using this technology, the amount of data must also be large. Ordinary database software like Oracle and SQL is not enough to handle so much data. Therefore, the terms “big data” and “data science” were created. Big data has had a considerable impact on the world, and data science has recently become one of the hottest topics. How are these two related now?
What is data science?
The scientific field combines different scientific methods and methods to study information technology. In a layman language, it is technically the science of studying data. This special field has developed rapidly over the years, and almost every university has professors and students studying and exploring this field.
Why is it so popular?
People always need to record the data people do, which will help predict the future and help to study the evolution of people’s lifestyles. It plays an important role in recording, managing and retrieving this data. There is a need to manage a large number of admitted patients, cars manufactured every day, and predict the weather conditions and future conditions in future years.
What else do you need to know?
From the examples given above, you must be aware that technology is everywhere. Do you know how Netflix knows movies and shows you might like? Well, this is entirely due to data science. It uses machine learning algorithms and methods to understand your requirements and help you stay one step ahead. The languages used in this field are Python, Java, SQL, etc. Before entering the world of data science, it is important that you master a large amount of math and computer science knowledge and these languages. Both can be considered as the basic requirements of the subject.
The demand for data science as a university course has increased, but unfortunately, since this is a very common field, there are no specific courses to follow in this area. Interestingly, data science has been confused with data analysis many times. If you face the same problem, you should know that the basic difference between these two areas is that in data analysis, people study the past of data. In data science, you not only have to study the past, but also study the present and the future. data. Data science is said to be the foundation of artificial learning, and everyone knows how artificial intelligence can bring dramatic entry into our lives.