Carto (formerly CartoDB) in Brooklyn, New York offers their location intelligence solution.
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IBM Environmental Intelligence Suite (EIS)
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The IBM Environmental Intelligence Suite is an AI-powered SaaS solution that provides intelligence to proactively manage the economic impact of severe weather and climate-change events built on weather data.
I have not seen a better mapping tool than CartoDB. You get the familiarity of Google Maps with arbitrarily complex geographic data visualization on top. CartoDB excels at large data sets where Google Maps API completely chokes when attempting to handle more than ~1000 data points. I was able to plot 500,000 points on a map with reasonable speed and able to perform complex aggregations to display boundaries of areas containing certain types of data, intersections of those sections, and more.
Given we are a larger accounting firm with clients in different geographical regions the tool was insightful but for smaller firms with a more robust business I'm not sure how useful the tool would be for those users. For our business the tool was specifically useful in the EMEA regions and how their climate impact differs from the US and the specific resourcing we need for it.
Presented meaningful charts and tables of our climate data in the 4 countries we operate and showed strengths and weaknesses across each market.
Formatted the presentation materials so our team did not have to take the reports and put them into a presentable format. We were able to leverage the technology's outputs in raw form which was very helpful and saved a lot of time.
Applied this to some of our client's data to see how we can better serve their business based off the different climates, environments, and countries they operate in (specifically within the real estate sector which is a large portion of our business).
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.
Given the newness of the platform we have struggled with the integration and onboarding as previously mentioned. Not only from getting our team members setup and able to use the platform but also integrating our current systems to be compatible we had to reach out to the customer support team quite a bit.
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.
