Standing at the counter as an elderly clerk hands over a dusty volume of county records is fast becoming a scene relegated to classic movies.
In previous posts, we talked about how the Open-Data movement has both revealed financial opportunities for natural resource professionals while instituting an era of data-driven accountability for environmental policy makers and regulators.
Another result of the Open-Data movement has been operational efficiency. The good news for government agencies that have moved vast amounts of environmental data to cloud-based systems is that they have slashed their budgets by drastically reducing internal spending on IT hardware and staff costs.
The better news from the environmental resource perspective is that ecosystem information gathering that used to take months via cumbersome and often expensive Freedom of Information Act requests is now available on demand. The EcoBlu Analyst cloud-based environmental big data efficiency tool was built to deliver that benefit.
EcoBlu Analyst subscribers have embraced operational efficiency by no longer visiting the clerk’s office or even mailing in information requests: they access vast amounts of environmental big data on-demand, from anywhere on their computer, tablet, or smartphone.
Learn how you can improve your own environmental data operational efficiency.
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WASHINGTON, DC – January 15, 2024, The National Environmental Banking Association and EcoBlu Analyst™ announce the release of a viewable/downloadable GIS ArcGIS layer of U.S. Mitigation and Conservation Banks, locations, contacts and more for the community of Esri users. This collection of geographic information and associated maps, apps, and data layers are additional resources for
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With government agencies and private companies adding vast amounts of routinely-isolated data in unrelated databases and still churning paper reports every day – databases, spreadsheets, and reports now exist in different formats, on different servers, and each with their own metadata and codes. Gathering and analyzing this data has become so expensive and time consuming
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