Analytics

Generating data is one thing, deriving knowledge and arriving at actionable insights is sweeter. Plumbing the depth of biology for meaningful actionable insights  —  insights that inform better decisions and strengthen hypothesis.

From concept to creation, Geschickten works with institutes and organizations to develop the analytic capabilities — from accessing and reporting on data to knowledge discovery —  to translate research into application.

Analytics is applicable to a wide variety of disciplines, including biology, medicine, environmental science, social science, government, and business. Analytics deals with planning, formulating, and collection of data. Following data collection, analytics offers techniques for measuring, describing, classifying, and computing the data. At its final stage statistical techniques can be used for cleaning, synthesizing, analyzing, and systematically interpreting acquired quantitative data.

In life Sciences, most of the time the data we collect is only a very small subset of the real world cases; therefore, it is necessary that all experiments pass through the rigor of statistical tests and processes to ensure that the result is statistically significant and can be generalized for the larger population.

 At Geschickten we work extensively with “R” - a framework that includes an object oriented programming language and the software environment for statistical computing and graphics. Though there are many statistical frameworks available in the commercial and research space, R is by far the most powerful statistical and graphics environment for scientific and biomedical data analysis.