08 Dec Modern GIS for the Enterprise
Esri’s customers are often trying to understand and solve some of the world’s most complex and challenging problems. The challenges of the past few years have been beyond extraordinary, with impacts spanning from local, regional, or even global audiences.
To understand the full scale of these problems, Esri have further redefined modern GIS by delivering a game changing enterprise system with geospatial capabilities and infrastructure available in the cloud, at the edge, and in the field.
Here are a few of the ways these advancements have been realized in ArcGIS this year.
Cloud–native geospatial infrastructure
In May, Esri released the newest product offering and next generation of ArcGIS Enterprise; ArcGIS Enterprise on Kubernetes. This new cloud native deployment option complements our existing ArcGIS Enterprise offering on Windows and Linux to deliver mapping and analytics in the public or private cloud, or on premises.
ArcGIS Enterprise on Kubernetes is supported in on-premises environments with Red Hat OpenShift Container Platform as well as in several cloud environments including Amazon Elastic Kubernetes Service (EKS), Google Kubernetes Engine (GKE), and Microsoft Azure Kubernetes Service (AKS).
This new offering brings scalability, resilience, and manageability to your organization. It also provides built-in high availability as well as flexibility to scale your infrastructure efficiently, reduces administrative overhead in managing deployments.
Integration with and connectivity to cloud–based data
You can connect to and use all the data stored in these clouds, like imagery in Amazon S3 or Azure Blob Storage, use Amazon RDS for PostgreSQL, Amazon Aurora or Google Cloud SQL for PostgreSQL or Microsoft SQL Server.
Powerful graph analysis capabilities
This year brought ArcGIS Knowledge, powerful new graph analysis capabilities to explore spatial and non-spatial relationships in ArcGIS Enterprise and ArcGIS Pro.
ArcGIS Knowledge enables organizations to identify and understand complex relationships found within vast amounts of data through maps, graphs, and histograms.
Geospatial AI
Geospatial AI applies spatial machine learning and deep learning techniques to help solve complex problems and derive deeper insights in powerful and innovative ways.
In ArcGIS, at the core of this technology is the arcgis.learn module in the ArcGIS API for Python which is used to train a wide variety of deep learning modules using your datasets.
Unleashing GIS Technology’s potential in every industries