Here is an example of how we have recently used open source data within our work, as well as integrated GIS techniques with Tableau.
One of our key clients wanted us to identify which of their install sites & customers may have been affected by Hurricane Sandy. Using open data GIS shape files available from the National Hurricane Centre (http://www.nhc.noaa.gov), we used Quantum GIS (http://www.qgis.org/) to extract the longitude and latitude points for pertinent storm surge and path data for Hurricane Sandy, and then shaped the data for use within Tableau.
We then looked at the intersection between the storm surge data, transactional data provided by our client, and external data-sets identifying key installations – and identified locations most likely to have been affected by the hurricane. Using the height of the storm surge combined with the storm path we created a probabilistic map of locations likely to have been affected, allowing the client to prioritise which sites to support.
Weather advisories are issued periodically for storms, in this case every 6 hours, with 31 advisories issued in total for Hurricane Sandy. The example dashboard shown below includes advisories 22-31. For this instance we’ve had to abbreviate the GIS detail available as Tableau Public only allows up 100,000 rows of data – but hopefully this provides an idea of what is possible to achieve combining locational/GIS data with business critical data & then representing within Tableau.