How to Choose an Effective Visual for Your Data Science Project

With a free downloadable guide to help you pick the right one

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Visual communication is a must-have skill for everyone that acts in a professional capacity. Decision making extensively relies on data, which comes in such volume that cannot be consumed in its raw format. So the need to apply some level of graphical abstraction is necessary.

Dataviz has emerged as a shared ‘language’ to curate data into a form easier to understand, highlighting patterns and outliers. While traditionally the business world draws a distinct line between storytelling and technical analysis, today corporations value those who cross between the two domains. The rise of the Citizen Data Scientist (a term coined by Gartner referring to a person who can perform simple or moderately sophisticated analytical tasks, but whose primary job function is outside the field of statistics and analytics itself) is a matter of fact.

Producing well designed, persuasive, and clear charts is a key competence for any Data Scientist, and it all starts by choosing the right type. This article will hopefully equip you with the basic visual ‘grammar’ to create compelling visualisations that powerfully portray your ideas.

There Is a Chart for That!