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What can be done with the data, once it has been collected? Two suggestions come to mind: analysis is the process by which we extract actionable insights from the data (this process is discussed in later posts), while visualisation is the process of presenting data, calculations, and analysis outputs in a visual format. Visualisation of data prior to analysis can help simplify the analytical process. Visualisation following analysis allows for the analysis results to be presented to various stakeholders

In this post, we focus on important visualisation concepts and methods; we shall provide examples of data displays to illustrate the various possibilities that might be produced by the data presentation component of a data analysis system.

Data Science Report Series #8: Data Visualisation and Representation (Draft), by Patrick Boily, Jennifer Schellinck, and Shintaro Hagiwara.

Post Author: Patrick Boily

Patrick is interested in the applications of mathematics and statistcs to evidence-based decision support. He has worked on 25+ such projects since 2008. He has extensive experience in data science, machine learning, A.I. and predictive analytics, data cleaning and data visualization.