Seven dirty secrets of data visualisation

Data visualisation - and in particular, web-based data visualisation - is having its moment. JavaScript libraries like D3.js, Raphaël, and Paper.js, building on modern browser support for Canvas and SVG, have made it easier than ever to produce complex visualisations that, until recently, were the province of computer scientists and a handful of specialist designers.

Visualisation is the new 'must-have' element in project proposals and personal portfolios, and startups like Platfora, Datameer, and our own employers ClearStory Data and Chartio are raising millions for analytics platforms with browser-based visualisation interfaces.

To some extent, the buzz is justified. Data visualisation is a wonderful way of exploring data, finding new insights, and telling a compelling story. But what are the real challenges visualisation developers face - and what don't they want you to know about their work?

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