How You Can Tell Stories About Your Data Through Visualization.

It is a well-established fact that data in its raw form looks pretty much messy to people who have no interest or understanding of the data. How then can we make data presentable and understandable to people of this sort?

“The ability to visualize data is an essential piece to the puzzle of data exploration and use … the fear data providers have of having their data trivialized, misunderstood or misrepresented also apply to the process of making visualizations, even simple ones … Visualizing data changes how data are understood and increases interest in data generally, which will encourage more and better data to be developed.” — Robert Kosara

Visualizing data has become an essential part of our lives as data scientists or analysts, artificial intelligence, and machine learning engineers. This is because we spend the majority of our time at work by explaining stuff to our colleagues or supervisors and making presentations on our work and findings. Data in its raw form most often looks just like a long list of random numbers, images, or audio files to people who have no knowledge or interest in it. Our job then is to be able to make these people make meaning out of the data we have and be able to guide them to make useful inferences out of the data we have. We tell stories of the past and future with the data we have but if we do not have visualizations, what then makes us different from soothsayers or crazy old oracles? In this article, I’ll take you through the importance of visualizing data, share some tips you can use to make your visualizations professional and some tools, libraries and software you can use to create elegant visualizations.