Introducing data science

Data science is a modern term that covers a large amount of different disciplines. We can think of data science as a field that uses various tools, processes, methods, and algorithms to extract knowledge and insights from data, which can be stored in a structured and unstructured manner. In one view, we can see data science as being quite similar to data mining.

Data science as a field includes everything that is associated with data manipulation—cleansing, preparation, analysis, visualization, and so on. Data science combines numerous skills that can be used for working with data such as programming, reasoning, mathematical skills, and statistics.

Data science is frequently mentioned together with other buzzwords such as big data, machine learning, and so on. As a matter of the fact, projects working with machine learning and big data are usually using data science principles, tools, and processes to build the the application.

Why is data science so important to us? Well, up until 2005, mankind had created approximately 130 exabytes of data (1 exabyte = 1,000 petabytes). But this number is growing quickly, and actually the amount of data created around the world is not growing in a linear fashion, but rather exponentially, with expectations that it will grow to 40 zettabytes in 2020. Such a large amount of data can hardly be processed by machines, or even data scientists, but a proper approach can increase the fraction of data that we'll be able to analyze.