Free Practice Questions for Esri EGMP2201 Exam

Geometric networks are not supported inbranch versioningor workflows where edits are moved directly to the base table. Therefore,traditional versioning without move edits to baseis the only viable option for implementing an offline mobile editing workflow with feature classes that participate in a geometric network.

1. Why Use Traditional Versioning Without Move Edits to Base?

Support for Geometric Networks:

Geometric networks are only compatible with traditional versioning workflows. Branch versioning does not support geometric networks, and using the "move edits to base" option bypasses the versioning framework required for geometric networks.

Offline Mobile Editing:

Traditional versioning supports creating replicas that allow offline editing and subsequent synchronization. This workflow is critical for mobile editing scenarios.

2. Why Not Other Options?

Branch Versioning:

Branch versioning is designed for feature services and web-based workflows but does not support geometric networks.

Traditional Versioning with Move Edits to Base:

This option moves edits directly to the base table, which is incompatible with geometric networks and versioning workflows that require offline editing.

Steps to Configure Traditional Versioning Without Move Edits to Base:

Register the feature classes and datasets (including geometric networks) with traditional versioning in ArcGIS Pro.

Create a replica to support offline editing workflows.

Synchronize edits back to the geodatabase after offline editing, reconcile, and post to integrate changes into the Default version.

References from Esri Documentation and Learning Resources:

Traditional Versioning Overview

Geometric Networks and Versioning

Conclusion:

Usingtraditional versioning without move edits to baseis the only method that supports offline mobile editing workflows while maintaining compatibility with geometric networks.

 Understanding the Scenario:

The query filters rows based on inspector_name and sorts the results by inspection_date.

Creating an index optimizes data retrieval by reducing the number of rows scanned during the query execution.

 Key Considerations for Indexing:

Primary Filter Column:The inspector_name column is the primary filter in the WHERE clause. Indexing this column ensures quick identification of rows matching the filter condition.

Sort Optimization:The ORDER BY inspection_date clause benefits from indexing inspection_date as the second column in a composite index, which accelerates sorting for the filtered results.

 Index Selection:

A composite index on inspector_name and inspection_date enables efficient query execution:

inspector_name ensures fast filtering.

inspection_date optimizes sorting.

Indexing unrelated columns like facility_type is unnecessary, as it is not part of the query.

 Steps to Create the Index:

In the enterprise geodatabase, use the database management tools or SQL commands to create a composite index:

CREATE INDEX idx_facility_inspections

ON facility_inspections (inspector_name, inspection_date);

 References:

Esri Documentation: Creating and Managing Indexes.

SQL Indexing Best Practices: Guidelines for composite index creation to optimize queries.

 Why the Correct Answer is D:A composite index on inspector_name and inspection_date directly addresses the query structure, optimizing both the WHERE filter and the ORDER BY clause.

 Understanding the Scenario:

The organization requires feature classes to beeditable in mobile and web apps.

Performance optimization through indexing is also needed for common queries.

 Feature Class Storage Options:

Enterprise Geodatabase:

Supports multiuser environments, making it suitable for mobile and web app editing.

Allows indexing at the database level, which improves query performance for large datasets.

Provides robust versioning, replication, and sync capabilities for mobile workflows.

File Geodatabase:

Supports single-user access and lacks enterprise-grade indexing and multiuser editing capabilities.

Does not meet the requirements for web and mobile app editing.

Mobile Geodatabase:

Optimized for mobile apps but does not support the enterprise-level indexing and multiuser workflows required for this scenario.

 Steps for Storing and Optimizing Feature Classes:

Store the feature classes in an enterprise geodatabase.

Create indexes on frequently queried columns to optimize performance for mobile and web app queries.

Use tools likeArcGIS Proto publish feature services for mobile and web app editing.

 References:

Esri Documentation: Enterprise Geodatabases Overview.

Indexing for Performance Optimization: Guidelines for improving query performance in enterprise environments.

 Why the Correct Answer is A:Enterprise geodatabases are the only storage option that supports multiuser editing in mobile and web apps and provides advanced indexing capabilities. File and mobile geodatabases lack the necessary functionality for this use case.

To ensure that editing and public usage do not affect each other, the best approach is tocreate separate database instancesfor these purposes.

1. Why Separate Database Instances?

Performance Isolation: Separating the databases ensures that editing operations (which are resource-intensive) do not impact the performance of queries or map services used by the public.

Workload Management: Editors can work in a dedicated environment with optimized settings for editing, while the public-facing database can focus on efficient querying and read-only access.

Security and Data Integrity: Public users are isolated from the editing environment, reducing the risk of unauthorized changes or accidental data loss.

2. How Separate Instances Work

Primary (Editing) Database: This instance supports editing workflows, including versioning, replication, and real-time updates.

Replica (Public) Database: A replicated copy of the primary database is maintained for public usage. Updates can be synchronized periodically using one-way or two-way replication.

3. Why Not Other Options?

Build New Feature Datasets:

Feature datasets organize related feature classes but do not separate editing and querying workloads. Performance issues would persist.

Separate Permissions for Public Services:

While restricting permissions helps secure data, it does not address performance issues caused by concurrent editing and public queries on the same database instance.

Steps to Create Separate Instances:

Set up aprimary database instancefor editing workflows.

Create areplica database instancefor public use by:

Using one-way replication to push updates from the primary to the public database.

Configuring the replica as read-only for public access.

Monitor and optimize each instance independently to ensure optimal performance.

References from Esri Documentation and Learning Resources:

Geodatabase Replication for Distributed Workflows

Managing Performance in Enterprise Geodatabases

Conclusion:

Creatingseparate database instancesensures optimal performance by isolating editing workflows from public usage, addressing both performance and security concerns.

Scenario Overview:

The user requires a standard database view of theroads feature classthat resides in a different geodatabase from the primary enterprise geodatabase.

Theroads feature classis frequently edited, and the user needs the view to recognize updates immediately.

Replica Types in ArcGIS:

One-way replicationwith thefull modelis suitable for scenarios where the parent geodatabase sends updates to the child geodatabase, and all schema and data changes are synchronized.

In thefull model, the child database retains versioning and acknowledges updates as they occur in the parent database, enabling the user to see immediate updates in their standard view.(ArcGIS Documentation: Geodatabase Replication Types)

Key Features of the Full Model:

Synchronizesboth schema and datachanges.

Suitable for feature classes withfrequent edits.

Ensures that the standard database view reflects updates immediately upon synchronization.

Alternative Options:

Option A:The simple model in one-way replication supports data-only synchronization and does not update schema changes, making it insufficient for dynamic environments.

Option C:Two-way replication is unnecessary since the edits occur only in the parent geodatabase.

Thus,one-way replication with the full modelis the appropriate choice to meet the requirement.

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

1. What is a Database View?

Adatabase viewis 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 ;

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.

References from Esri Documentation and Learning Resources:

Creating and Using Database Views

Data Security in Enterprise Geodatabases

Conclusion:

Adatabase viewis the most effective method to restrict access to specific fields in a feature class, ensuring data security while providing flexibility in data sharing.

The slow performance at zoomed-out extents is likely caused by the rendering of complex polygon geometries in real time, which can be computationally intensive. Using cached data is the best approach to improve performance in this situation.

1. Reason for Slow Performance at Zoomed-Out Extents

Complex polygons require significant processing power to render at smaller scales due to the high number of vertices and complex geometry.

When users zoom out, the number of features being displayed increases, causing additional strain on the map service.

Attribute queries are not affected because they do not involve rendering the geometries.

2. Advantages of Using Cached Data

Cached tiles are pre-rendered images of the map at specific scales, stored on the server.

When cached data is used, the server simply retrieves and displays these images instead of dynamically rendering the features.

This drastically reduces server load and improves map performance at zoomed-out extents.

3. Why Not Other Options?

Run the Analyze Datasets Tool:

This tool checks for issues like invalid geometries, missing spatial indexes, or improper field types. While useful for general data health, it does not directly address rendering performance.

Compress the Enterprise Geodatabase:

Compression improves performance for versioned data by consolidating states and cleaning up the database. However, in this case, the feature class is not versioned, so compression would not resolve the rendering issues.

Steps to Implement Caching:

Open ArcGIS Server Manager and navigate to the map service configuration.

Enable tile caching and define the scales at which tiles should be created (include the problematic zoomed-out extents).

Generate the cache using the "Manage Map Server Cache Tiles" tool.

Test the map to ensure performance improvements.

References from Esri Documentation and Learning Resources:

Map Caching in ArcGIS Enterprise

Best Practices for Map Services

Conclusion:

The GIS administrator should recommend enablingcached data for the zoomed extentsto significantly improve map performance.

 Understanding the Scenario:

The GIS analyst needs to share a large repository oflidar data.

The data includes surface constraints like breaklines, which are used to enforce terrain or surface rules.

 Dataset Types Overview:

Mosaic Dataset:Designed for managing large collections of raster data, such as imagery or elevation grids. It is not specifically optimized for lidar point cloud data.

Feature Dataset:A container for related feature classes in a geodatabase. It is unrelated to managing lidar data or surface constraints.

LAS Dataset:A specialized dataset designed for managing lidar point clouds. It supports point classification, surface constraints (like breaklines), and efficient querying or visualization of lidar data.

 Steps to Create and Share a LAS Dataset:

Create a LAS dataset in ArcGIS Pro and add lidar files (LAS or ZLAS format).

Define surface constraints (breaklines) in the LAS dataset properties.

Share the LAS dataset as a service or package for organizational access.

 References:

Esri Documentation: LAS Datasets.

Managing Breaklines in LAS Datasets: Instructions for incorporating surface constraints.

 Why the Correct Answer is C:LAS datasets are explicitly designed for managing and sharing lidar data with surface constraints like breaklines. Mosaic and feature datasets are unsuitable for this purpose.

Scenario Overview:

An editor updates500,000 recordsin achild versionof the Default version using a field calculation.

Another editor updates the Default version, and thechild version is reconciledwith Default.

What Happens During Reconciliation?

In traditional versioning, edits to feature classes are stored in theAddsandDeletes tables.

During reconciliation:

Changes in the child version that differ from the Default version areduplicatedin the Adds and Deletes tables to track the differences.

This allows conflicts to be detected and resolved while preserving all edits.(ArcGIS Documentation: Traditional Versioning Workflow)

Alternative Options:

Option B: They will be migrated to the Base table

Migration to the base table occurs only when changes are posted and the geodatabase is compressed.

Option C: They will be removed from the States repository table

The States repository table tracks state transitions and is unaffected during reconciliation.

Thus, during reconciliation, the500,000 records are duplicated in the Adds and Deletes tablesto manage and detect conflicts.