So much of the world's data is now location-enriched, resulting in a big opportunity to extend location intelligence techniques to conventional big data analytics processes. Equally, geospatial-specific processes in GIS tools are becoming too slow for today's data volumes. MapD bridges this divide by making geospatial capabilities a first-class citizen of our extreme analytics platform. With MapD, geospatial analysts can interactively explore up to millions of polygons and billions of mapped points, and business analysts can now easily incorporate spatio-temporal analysis in their regular big data analytics workflows.
A Forbes article reported that “66% of enterprises rank location intelligence as either critical or very important to revenue growth strategies.” Yet, mainstream GIS platforms struggle to analyze more than a few hundred thousand data points, and then only with latency that makes visual exploration of GIS data incomplete, slow and uncomfortable. The need for advanced geospatial analysis tools is now greater than ever.
In milliseconds, you can cross-filter billions of location data records alongside other features, to understand location in context of your mission. MapD stores geographic data types (POINT, LINESTRING, POLYGON, and MULTIPOLYGON) in native form, so you can run massive parallel calculations on geo data to optimize logistics routes or see how many U.S. schools are within flood zones (for example).
The MapD Core SQL engine natively stores geographic and geometric data types (POINT, LINESTRING, POLYGON, and MULTIPOLYGON). This enables you to run geo calculations with the massively parallel supercomputing speed of GPUs. Because polygons are rendered natively on the backend, you can interactively explore millions of shapes on a chart in a web browser. Speed and power come from MapD’s back end.
You probably spend hours prepping your GIS data and selecting features for analysis. This data prep involves tedious, row-by-row exploration--not what you dreamed of when you chose this profession. You’d rather spend less time getting data ready and more time turning it into insights, recommendations and actions.
MapD was created for geospatial analysis accelerated by graphics processing units (GPUs). Our analytics platform speeds data exploration with extraordinarily fast SQL queries, rendering and visualization. You can import native geo data into MapD, explore it visually, and clean it quickly, so it’s ready for analysis and reporting to your colleagues.
Read this blog post by MapD’s Veda Shankar. Veda explains how to use the MapD Immerse visualization system to explore data, with powerful cross-filtering. Geospatial analysts can use this type of zero-latency exploration of very large geo data to understand the dataset and prepare it for further use.
You rarely work alone. Even if you are the only geospatial analyst in the company, you must share geospatial findings with co-workers, clients and partners who don’t understand cartography or spatial analysis. You may discover great insights, but they will only be as valuable as your ability to communicate them to others.
MapD visualization makes it easy to share geo charts and geospatial calculations with others. If you find a better transportation route, a real estate opportunity, or an enemy on the battlefield, you can show it to others in real time. Object-level permissions let you share geospatial data and dashboards without worrying about view permissions. We take care of that for you on the backend.
Your geospatial analysis becomes more valuable as more people can see it, interact with it and understand it. Some charts may contain sensitive information and this can make sharing seem dangerous. MapD solves this by decoupling object-level view permissions from the ability to share interactive dashboards with others.