Communicating Data Science Findings

Learn how to effectively communicate data science analyses.

Data Science is as much about storytelling as it is about coding and data wrangling. The reason Data Scientists are in such high demand recently is because of their abilities to translate the performance and health of a company by gathering previously unavailable insights from its data. It might seem like an easy and obvious thing at the moment, but in reality, a company’s data might be so jumbled and unstructured that mere mortals are unable to make any sense of it.

Best Practices for Communicating Data Science Findings

A Data Scientist explaining to a group of Product Managers that the covariance between two variables shows no visible linear relationship is like Dumbledore teaching a group of Jedi how to conjure up a Patronus. Two different worlds. Does not compute.

The transformation of data analysis results by Data Scientists into easily accessible and understandable mediums for everyone to understand is actually one of the most important skills on the job.

After a Data Scientist completes an in-depth investigation on some set of data, the results of this investigation need to be converted somehow into a simplified summary for others to observe and understand. Usually, these kinds of summaries are written up as comments to one of your assigned tickets or more often as slides in a presentation that you then verbally discuss in further detail.