Abstract
The article describes the modern escalation of “big” and open data; situations where sociologist needs new competences such as coding and programming are analyzed. The author puts attention to two key research strategies when dealing with big data: self-localization and dipping into data. The first strategy refers to the researcher’s focus on traditional sociological analysis restricted by small sample size; the second one implies maximal use of the growing open source data. The challenges a researcher has to face when dealing with big data are as follows: (1) data extraction; (2) data processing and improvements; (3) data visualization. This is why a researcher should master coding and programming. Sociologists with humanitarian education should choose R statistical environment and Python programming language becasue they have simple syntax and allow solving complicated data processing, analysis and visualization tasks. The article provides examples of scripts as a demonstration of the possibilities of the R and Python programming languages.
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