What Is Data Science?

The field of data science is rapidly growing, but defining data science is a struggle to most. With the rise of machine learning and artificial intelligence technology, data science exploded from 2011-2012. During this year, job listings for “data scientist” increased by 15,000%; however, the field has been navigating to the mainstream for nearly 3 centuries.

Data science requires skills in computer science and mathematics that are instrumental to the development of predictive, industrial machine learning and Enterprise AI. To perform, data scientists use heterogeneous data to solve complications and analyze data. In short, the process of data analysis has three steps: preparation, testation, and communication.

Data scientists must first capture and extract their data to store and stage it. This data is then mined and classified. Scientists then move on to the testing phase, directly applying the data to the field. This entails a standard process of hypothesizing test theories based on visual interpretations of data and analyzing models, exploring further into research to derive the meaning of the data.

Finally, data scientists simply need to communicate their findings. This can be done by visually- such as creating a picture to model predictions, or physically applying the data to ensure effectivity within the business.

Although data science is a popular field today, it has immense depth. Read more on the role of data science in technology below.