Latest Contributions by SpatialNinja

Great new updates this month.  Here are some of my favorites: Custom login landing page.  Users can new pre-set which group, gallery, home page, or content to default to after they login. Insights for ArcGIS.  Insights for ArcGIS is now available in ArcGIS Online. Lean more here:  Insights for ArcGIS is now available in ArcGIS Online | ArcGIS Blog  Feature Editing Permissions.  New settings available for editing features in a feature service. Workforce for ArcGIS.  Information entered into a workforce assignment can now be passed into Collector and added to a feature collected.  Operations Dashboard. New web version of Operations Dashboard. Yay! See all the updates: What’s New in ArcGIS Online (December 2017) | ArcGIS Blog  ... View more

Esri is partnering with ETI Software to show how you can improve your organizations performance with GIS powered operational intelligence.  Improving service delivery, reducing cost and enhancing customer experience requires networks and organizations capable of operating at peak levels of performance. Many organizations don’t have an operational intelligence system capable of processing and analyzing the complex data inputs generated from their OSS/BSS. An operational intelligence system that uses GIS technology can leverage the Science of Where to transform this data into information and deliver it to key decision makers. Take advantage of this free webinar and learn how your organization can benefit from using GIS powered operational intelligence. Register here: http://go.esri.com/OpIntel121317 ... View more

Machine Learning (ML) refers to a set of data-driven algorithms and techniques that automate the prediction, classification, and clustering of data. Machine learning can play a critical role in spatial problem solving in a wide range of application areas, from image classification to spatial pattern detection to multivariate prediction. In addition to traditional Machine Learning techniques, ArcGIS also has a subset of ML techniques that are inherently spatial. These spatial methods that incorporate some notion of geography directly into their computation can lead to deeper understanding. The spatial component often takes the form of some measure of shape, density, contiguity, spatial distribution, or proximity. Both traditional and inherently spatial machine learning can play an important role in solving spatial problems, and ArcGIS supports their use in a number of ways. Machine learning can be computationally intensive and often involves large and complex data. Esri’s continued advancements in data storage and both parallel and distributed computing make solving problems at the intersection of ML and GIS increasingly possible.  Learn some examples from this ArcGIS blog: Machine Learning in ArcGIS | ArcGIS Blog  ... View more

From the Esri family to yours.  Mapping the Thanksgiving Harvest  ... View more

Happy GIS Day to all the GIS professionals in telecom & utilities.  Here are some fun resources to share with your organizations to help spread your passion for GIS. GIS Day Resources: GIS Day November 15, 2017 - Discovering the World Through GIS  The Science of Where: http://arcg.is/0uzr9j  The Language of Spatial Analysis: http://arcg.is/yK4O1  GIS in Telecom Videos: Telecommunications - YouTube  GIS in Utilities Videos: Electric and Gas - YouTube  ... View more

Migrating to a Software-Defined Networks (SDN) and Network Function Virtualization (NFV) architecture is a forgone conclusion for telecommunications companies. Technology Business Research predicts that investment in SDN and NFV technology will reach $168 billion by 2022. Despite this inevitability, many telecommunications service providers are struggling to determine where to deploy this technology to maximize their return on investment. Learn how location and spatial analysis can assist: https://www.linkedin.com/pulse/telecom-future-optimizing-your-nfvsdn-investment-randall-frantz/  ... View more