EAEP2201 Exam Dumps : Enterprise Administration Professional 2201

ArcGIS GeoAnalytics Server is designed to perform distributed analysis on large volumes of spatial and temporal data. To efficiently process large datasets, it is recommended that each machine in the GeoAnalytics Server site has at least 16 GB of RAM and 4 CPU cores. However, for optimal performance, especially when handling very large datasets, increasing the available RAM can significantly improve processing times.​

In this scenario, the machine already has 16 GB of RAM and 4 cores. Adding more RAM would allow the GeoAnalytics Server to allocate more memory per job, enhancing its ability to process large datasets efficiently. Therefore, the recommended action is to add 16 GB of RAM to the GeoAnalytics Server machine.​

Reference Source: ArcGIS Enterprise documentation on GeoAnalytics Server system requirements and performance optimization.​

The correct solution is to place ArcGIS Enterprise in read-only mode. This is an administrative function designed specifically to prevent changes to content or configuration while still allowing users to view and access existing items.

From the official ArcGIS Enterprise documentation:

“Read-only mode allows an administrator to restrict changes to the portal. When enabled, no users (including administrators) can create, update, or delete items, groups, or users. However, users can still search for and view items, access content, and use apps and services.”

This feature is typically used during maintenance windows or before performing disaster recovery tasks to preserve system state.

Option B is incorrect because changing user roles to Viewer would not prevent content changes by administrators or other roles with publishing privileges.

Option C refers to cloning, which is not a preventive or temporary access control measure, but rather a method for standby deployments or replication.

Option D (disabling the Web Adaptor) would disrupt access entirely, which does not match the requirement to allow viewing.

The Spatiotemporal big data store is designed for massive datasets and optimized for high-speed visualization, time-enabled querying, and big data analytics. It is ideal for storing millions of point features such as sensors or oil rig locations, especially when performance and scalability are critical.

From ArcGIS documentation:

“The spatiotemporal big data store is designed for writing and querying large volumes of spatial and temporal data. It’s optimized for visualizing high-density datasets in web maps.”

Option B (Relational) works for moderate data volumes but may not scale well.

Option C supports cached tiles, not dynamic feature access.