Data science is a multidisciplinary field that includes statistics, computer science, machine learning, and domain expertise to get knowledge and insights from data. Data science usually ends up developing a data product. A data product is the changing of the data of a company into a product to solve a problem. The term “data science” has become a buzzword and is now used to represent many areas like data analytic, data mining, text mining, data visualizations, prediction modeling, and so on.

R is a programming language used for data manipulations, statistical analysis, and data visualization. Just like any programming language, R includes conditional statements, recursive functions, and input/output commands. But unlike a typical programming language, R includes the following features that make the language especially suited for data science. With thousands of R packages are available, it is not surprising that R is increasingly becoming a de facto language of data science. Unlike many of the commercial statistical packages that are geared towards a particular audience (e.g. SPSS is geared towards statistical analysis of quantitative data in business and social sciences), R is used across many industries and scientific disciplines

The latest R software is available in the openSUSE repository. But we need special customization (enable memory profiling, R-shlib, with blas, lapack, etc.). Finally, we have install R from the source code on openSUSE Leap 15.1. After installing Rstudio and adding the R packages, we got a powerful data science environment.

In this talk, attendees will get to know about data science environment with R on openSUSE Leap 15.1