Resumen Diseñar con datos parece sencillo: haces un test A/B y te quedas con la solución que más conversiones tenga ¿cierto? pero ¿somos conscientes de lo que nos dicen los datos? ¿cómo sabemos qué conviene evaluar? ¿qué hacemos si los resultados contradicen nuestras ideas originales? ¿Hay vida (y datos) más allá de los tests A/B? En esta charla me gustaría compartir algunas ideas y experiencias...
Data-ink ratio establishes that every pixel used to represent data must be non-redundant and non-erasable, meaning that if the ink is removed from the image, the graphic will lose the content. That Tufte’s principle can be understood very quickly with this example gif image: Darkhorse Analytics On this occasion, I’m going to take a risk and forcing me to find examples...
Hospital Costs
The federal government recently released data about what hospitals charge for procedures, and how much Medicare reimburses them. We have visualized some of this data, along with publicly available data about mortality rates under these same procedures. How does your hospital stack up against national averages?
I'm UX/Product Designer at Ebury. I have a chaotic side project called Cinefilica and founded the most interesting tech community in Málaga: Yes We Tech. I enjoy writing random thoughts on UX, Design, Technology and Society. Something I should know? Comment on my blog, Twitter or email me to carmel.hassan@gmail.com