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CartoDB - Great tool for geospatial data viz
December 09, 2016

CartoDB - Great tool for geospatial data viz

Diana Lam | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with CartoDB

As an analyst at an economic development consulting firm, I frequently analyzed and visualized demographic data. My organization did not use CartoDB as a whole, but analysts were allowed to use whatever tools they wanted to produce work, and so I decided to use CartoDB because of its ease of use. I primarily used the software to generate chloropleth maps to visualize different pieces of demographic data across zip codes. Without CartoDB, we typically made these maps manually or using other software that didn't have as much visual customization as CartoDB.
  • SQL integration - CartoDB supports SQL, so you can use SQL to do different types of data munging and analysis, which makes it easier to do more complex visualizations of data than just using the column/row interface. It also uses common programming data structures (string, float, etc.) which makes it easy to parse data types.
  • GEOJSON compatibility - The software comes out of the box with common maps that you might want to use, but you can upload your own GIS or GEOJSON files to create custom maps.
  • Out of the box visuals - The default settings/options for map creation over most of the bases of what you might want to do. The out of the box color schemes and design are great.
  • Learning curve - CartoDB might be difficult to use if you don't have a bit of SQL or data structures background. If you're not familiar with floats, strings, etc., you might upload an Excel file and be confused about how to manipulate it to get the software to create the maps that you want.
  • Performance - When I used it, there were some occasional issues with loading and parsing large data files.
  • CartoDB definitely saves a lot of time when creating visualizations. Previously, I would use different software and have to make edits manually (or just create the visualizations manually to start with). I would say that the software definitely cuts the time required to create certain visualizations by a half or two-thirds.
Python is definitely a more powerful tool for data munging and analysis, but the python packages for geo-related data viz (bokeh, matplotlib, seaborn) are cumbersome to use. I would recommend doing your data analysis in Python and then exporting the final data to CartoDB for visualization. One benefit of doing this is that CartoDB can automatically publish your viz to a link or object, so you don't have to export it and host it yourself. Another benefit is that CartoDB automatically updates the viz once you change the data, eliminating the need to continuously regenerate image files.

I haven't used Tableau too extensively, but from the experience I've had with it -- Tableau is better suited for traditional analytical visualization (charts, graphs, etc.) than for geospatial mapping and visualization.
CartoDB is great for generating geographic visualizations of data where the geographies are well-defined. It would be great for analysts to develop visualizations of data with spatial elements. That being said, the software is limited if you want to do any real data munging or analysis, as it can be cumbersome to use and there isn't a great interface for actually saving the results of different manipulations (you can save it as a new file, but it's hard to do version control, etc.). I would recommend preparing the data outside of CartoDB and only using the tool for visualization once the data is well prepared.