Ever since the beginning of human civilisation, data has been produced. But it hasn’t been until recently that we’ve been able to unlock its full potential and learn from it. We have only recently begun to think of data as an industry’s fuel. The increase in computer capacity is the fundamental driver of this most recent revolution.

A data scientist uses information to understand, clarify, and support business decision-making. There are numerous methods for gathering information or proof. Scientists can collect their data through making observations of the natural world, conducting laboratory experiments, or using computer models. Scientists choose which approach to take, frequently combining approaches. They then devise a mechanism and compile their information.

Scientists utilise a variety of tools, such as tabulation, graphical interpretation, visualisation, and statistical analysis, to find the relevant aspects and patterns in the data because, in most cases, the facts do not speak for themselves. The degree of certainty is calculated after error sources are found. To aid scientists in interpreting the data, raw data are compiled and arranged using spreadsheets, databases, tables, graphs, and/or statistical analysis. Measurements and descriptions can be used to create either quantitative or qualitative data .