Full meal deal
This petroleum workflow (step-by-step here) is common to day-to-day operations: download unformatted well data, load it into a petrodata standard format, and post on a map &/or on the web with attendant infrastructure:[Click all images to enlarge]
Extract:
Transform:
And load:
Smorgasbord
The address workflow consisted of spotting points handed as a CSV file, within a perimeter handed as a JSON file. My friend has no geodata tools and looked at it as a Big Data exercise: The sample has thousands and hundreds of address and perimeter points, respectively, but the study area may have an order of magnitude or two more... like my Tall ships historic weather map at local scale!Address file to GIS:
Convert JSON file:
Perimeter & intersect:
Overlay and output:
"Ben Franklin"
That's when two item lists to compare, are shown against relevant criteria (a variant is to have one item list, shown against pros & cons). Reading cadastral files from geoportail.gouv.fr can be done with professional tools like in the first exercise.And there may be other tools, say R and Python to do that directly, but then again that's another skillset business users may/not have:The point here, however, is a lowest-barrier-to-entry for geo-processing, which is but a means to an end...
"Look before you leap"
The reason I teamed up with LINQ, is to provide a listen-and-process tool, from which will cascade the workflows then, and only then the tools. These are two examples from the top and the bottom range of the tech stack to meet specific day-to-day business operational needs.Note: the petroleum workflow is widely posted, and available under Creative Commons. The address workflow is not, as suggested by the anonymised illustrations.
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