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Go to:Introduction For companies engaged in oil and gas exploration, getting fast access to high resolution data is an important enabler for finding the right locations to drill a well before their competitors. We worked to pioneer a solution for interactive 3D visualizations of oil basins using datasets containing over 100 billion data points – as…
The problem is widely felt. As data collection has mushroomed, traditional data systems struggle to produce timely alerts to problems and other real time events. Financial organizations want to be able to spot fraud, or maintain a running tallies of risk and exposure. Tracking systems need to flag when vehicles leave pre-determined paths or allow…
Spatial data analysis is computationally intensive. Most solutions grind to a crawl at a few million points. But recent advances in parallel computing create opportunities to challenge these computational constraints. Kinetica’s vectorized spatial function library can perform computations on the fly on massive amounts of spatial data. Matthew Brown shows us some of these capabilities…
Our sat nav gives us options of the shortest route home, or avoiding tolls or highways. But what if we want the most scenic route home, or the most well-lit? Learn how to do this using a road networks as graphs, geo-spatial features as graph networks and graph optimizations.
Geospatial data is any data that has a geographic component to it. A geographic component simply implies a location (or a set of locations) that can take the form of simple points on a map with latitude and longitude coordinates or more complex shapes that describe lines and boundaries, or even elevation. Examples could include…