Free Esri EGMP2201 Exam Dumps May 2026

Understanding the Scenario:

A two-way replica exists between a parent geodatabase and a child geodatabase to share edits.

A schema change (adding the legal_area field) occurs in the parent geodatabase but is not applied to the child geodatabase.

The parent synchronizes the replica, attempting to push changes that include edits to the new field.

Replica Synchronization Behavior:

Schema Changes and Replication: Replication does not automatically synchronize schema changes such as adding new fields. Schema updates need to be manually applied to both parent and child geodatabases before synchronization.

Conflict during Synchronization: If schema changes (like adding a field) are made in the parent geodatabase but not replicated in the child geodatabase, synchronization attempts to apply edits referencing the missing field. This results in an error because the child geodatabase does not recognize the new field.

Reference:

Esri Documentation: Schema Changes and Replication.

Error Handling in Synchronization: Guidance on managing synchronization issues due to schema mismatches.

Why the Correct Answer is A: During synchronization, an error occurs because the legal_area field does not exist in the child geodatabase. Synchronization cannot succeed unless both replicas have compatible schemas.

Scenario Overview:

Editors are spending multiple hours resolving conflicts during reconciliation.

Key points:

Conflicts are detected by attribute (not by object).

Traditional versioning is used.

Weekly compression and weekly reconcile/post workflows are in place.

Why Reconcile and Post Daily?

Conflicts occur when multiple editors make overlapping edits. The longer versions remain unreconciled, the more conflicts accumulate, leading to time-consuming resolution.

Daily reconciliation and posting minimizes the number of changes between the parent and child versions, reducing the likelihood and volume of conflicts.

(ArcGIS Documentation: Reconcile and Post)

Key Benefits of Daily Reconciliation:

Fewer Changes to Compare: With fewer edits accumulated in each version, conflict detection is faster.

Less Complex Conflicts: Simplifies resolution since changes are smaller and more recent.

Improved Editor Productivity: Editors spend less time resolving conflicts, freeing up time for other tasks.

Alternative Options:

Option A: Detect conflicts by object

While this may reduce conflict granularity, it can lead to overwriting valid edits at the object level, which may not be acceptable in collaborative workflows.

Option B: Compress the geodatabase daily

Compression reduces the state tree and improves performance but does not directly reduce the number of conflicts during reconciliation.

Therefore, implementing daily reconciliation and posting is the most effective way to reduce conflicts and improve editing efficiency.

To restrict access to specific fields in a feature class, the GIS data administrator should use a database view.

1. What is a Database View?

A database view is a virtual table created by a SQL query. It displays data from one or more tables or feature classes, but only the specified fields and rows are accessible.

Views allow the administrator to control the fields and records visible to users without altering the underlying data.

2. Why Use a Database View?

Provides fine-grained control over data access by limiting which fields (or rows) are visible to specific users.

Helps enforce data security policies in multi-user environments.

Can be shared as a read-only layer or with restricted update permissions, depending on the use case.

3. Why Not Other Options?

Layer File:

A layer file (*.lyr) only defines how data is symbolized and displayed. It does not restrict field access at the database level. Unauthorized users can still access hidden fields through direct database connections.

Query Layer:

A query layer allows for custom SQL queries when displaying data in ArcGIS but is not a security measure. Users can modify or bypass the query to access all fields.

Steps to Create a Database View:

Use SQL to define the view, specifying only the required fields:

CREATE VIEW restricted_view AS

SELECT field1, field2

FROM feature_class

WHERE <condition>;

Grant permissions to the view for authorized users while restricting access to the base table.

Publish the view in ArcGIS as a read-only layer if needed.

Reference from Esri Documentation and Learning Resources:

Creating and Using Database Views

Data Security in Enterprise Geodatabases

Conclusion:

A database view is the most effective method to restrict access to specific fields in a feature class, ensuring data security while providing flexibility in data sharing.

Understanding the Scenario:

An enterprise geodatabase feature dataset is accidentally deleted.

The organization needs to recover the dataset to its original state.

Available Technologies:

High Availability: High availability setups (e.g., failover systems) ensure continuous access to geodatabases during hardware or software failures. However, high availability does not restore accidentally deleted data.

Backup: A backup is a snapshot of the geodatabase taken at a specific point in time. It allows administrators to restore deleted datasets or recover from data loss scenarios.

Archiving: Archiving tracks historical edits in versioned geodatabases but does not provide recovery for accidentally deleted datasets.

Steps to Recover the Dataset:

Identify the most recent backup of the enterprise geodatabase.

Restore the geodatabase or extract the specific feature dataset from the backup.

Verify the restored data and synchronize it with ongoing updates if necessary.

Reference:

Esri Documentation: Backup and Restore.

Best Practices for Data Protection: Guidelines for implementing regular backups to prevent data loss.

Why the Correct Answer is B: A backup is the most reliable solution for recovering an accidentally deleted feature dataset. High availability ensures uptime but does not address data recovery, and archiving tracks edits rather than preserving entire datasets.