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Esri Enterprise Geodata Management Professional 2201 Sample Questions (Q44-Q49):

NEW QUESTION # 44
A GIS analyst creates a join relationship between a large dataset and a nonspatial table to calculate an attribute field. Upon building the join, the analyst receives an error message stating that the join field <value> in the join table <value> is not indexed.
Which tool should the analyst run?

A. Add Spatial Index
B. Add Attribute Index
C. Rebuild Indexes

Answer: B

Explanation:
Scenario Overview:
* The analyst creates a join between a large dataset and a nonspatial table to calculate an attribute field.
* An error occurs, indicating that the join field is not indexed.
Cause of the Problem:
* Joins between datasets rely on indexed fields to optimize the join operation. Without an index, the system must perform a full table scan, which can lead to errors or slow performance when working with large datasets.
Solution:
* Running theAdd Attribute Indextool creates an index on the join field, enabling efficient joining operations.(ArcGIS Documentation: Attribute Indexes) Steps to Resolve:
* Open theAdd Attribute Indextool in ArcGIS Pro.
* Select the nonspatial table as the input dataset.
* Choose the field used in the join operation as the field to index.
* Run the tool to create the attribute index.
Alternative Options:
* Option A:Add Spatial Index is irrelevant for nonspatial data.
* Option C:Rebuild Indexes reorganizes existing indexes but cannot create new ones, which is required here.
Thus, the analyst should run theAdd Attribute Indextool to resolve the error.

NEW QUESTION # 45
A GIS analyst needs to visualize a centralized folder of imagery with multiple images in ArcGIS Pro. The administrator needs to prepare for this imagery to be accessed across the organization within the enterprise geodatabase.
Which storage mechanism should be used?

A. Mosaic dataset
B. Raster catalog
C. Raster dataset

Answer: A

Explanation:
Amosaic datasetis the most appropriate storage mechanism for visualizing and managing a centralized folder of imagery, especially when the imagery is to be accessed across an organization through an enterprise geodatabase.
1. What is a Mosaic Dataset?
* A mosaic dataset is a geodatabase structure optimized for managing and serving large collections of raster data, such as satellite imagery or aerial photographs.
* It provides dynamic mosaicking, rendering, and query capabilities.
2. Why Use a Mosaic Dataset?
* Centralized Management: A mosaic dataset can reference multiple images stored in a folder without duplicating the data, maintaining a centralized source of imagery.
* Scalability: It supports large collections of raster data and allows for efficient querying, rendering, and analysis.
* On-the-Fly Processing: Provides options to apply image processing and rendering rules without modifying the source data.
* Enterprise Access: Mosaic datasets stored in an enterprise geodatabase can be published as image services for access across the organization.
3. Why Not Other Options?
* Raster Dataset:
* This option is for storing a single image or raster layer in the geodatabase, not suitable for managing multiple images.
* Raster Catalog:
* Raster catalogs organize rasters but lack dynamic mosaicking, rendering, and query optimization capabilities. They are less efficient and are now considered outdated in favor of mosaic datasets.
Steps to Create and Use a Mosaic Dataset:
* OpenArcGIS Proand connect to the enterprise geodatabase.
* Create a new mosaic dataset using theCreate Mosaic Datasettool.
* Add rasters to the mosaic dataset using theAdd Rasters to Mosaic Datasettool, pointing to the centralized folder of imagery.
* Publish the mosaic dataset as an image service in ArcGIS Enterprise for organization-wide access.
References from Esri Documentation and Learning Resources:
* Mosaic Datasets Overview
* Managing Imagery with Mosaic Datasets
Conclusion:
Amosaic datasetprovides the best functionality for managing, visualizing, and sharing multiple images from a centralized folder within an enterprise geodatabase.

NEW QUESTION # 46
A database administrator needs to move the enterprise geodatabase to a new server. The new enterprise geodatabase must be kept intact.
Which process should be used?

A. Two-way replication
B. Export to file geodatabase
C. RDBMS export/import

Answer: C

Explanation:
To move an enterprise geodatabase to a new server while keeping it intact, theRDBMS export/importprocess is the appropriate method.
1. Why Use RDBMS Export/Import?
* Enterprise geodatabases are tightly integrated with the underlying RDBMS (e.g., SQL Server, PostgreSQL, Oracle). Exporting and importing the entire database ensures that:
* All geodatabase configurations (e.g., tables, indexes, metadata) are preserved.
* No data integrity is lost during the migration process.
* This method maintains the geodatabase's structure and relationships.
2. Why Not Other Options?
* Export to File Geodatabase:
* While exporting to a file geodatabase allows for data transfer, it does not preserve the enterprise geodatabase structure, including user permissions, versioning, and replication configurations.
* Two-Way Replication:
* Replication is designed for synchronizing data changes between geodatabases, not for moving an entire geodatabase to a new server. It may also leave some administrative configurations behind.
3. Steps for RDBMS Export/Import
* Export the Database:
* Use the RDBMS tools (e.g., pg_dump for PostgreSQL, SQL Server Management Studio) to create a full backup of the geodatabase.
* Ensure all related schemas, indexes, and metadata are included.
* Import to the New Server:
* Set up the RDBMS on the new server and configure it for enterprise geodatabases.
* Import the backup file to restore the geodatabase on the new server.
* Post-Migration Steps:
* Reconfigure connections in ArcGIS Pro or ArcGIS Server to point to the new geodatabase.
* Test to ensure all functionality works as expected.
References from Esri Documentation and Learning Resources:
* Backing Up and Restoring an Enterprise Geodatabase
* RDBMS Tools for Backup and Restore
Conclusion:
TheRDBMS export/importprocess ensures a complete migration of the enterprise geodatabase to a new server while preserving all configurations and data integrity.

NEW QUESTION # 47
A user wants to share a frequently edited points feature class as a web layer. The points contain sensitive attributes and will be read-only for online viewers.
The following workflow is applied:
* Points is registered as versioned
* A standard database view is created for points, which hides the sensitive attributes
* The view is published as a web layer from the Default version
As the points feature class is edited throughout the week, edits are not visible in the web layer.
What should the GIS administrator do?

A. Alter the view to use a versioned view as the source
B. Rebuild indexes and calculate database statistics on points
C. Have all editors reconcile and post points edits to Default

Answer: A

Explanation:
The issue arises because the standard database view is based on the base table of the points feature class, which does not include edits made in child versions. To resolve this, the database view must reference a versioned viewto reflect changes in the Default version.
1. What Is a Versioned View?
* Aversioned viewis created when a feature class is registered as versioned.
* It allows querying and editing versioned data, including edits made in the Default version and child versions.
* A standard database view does not account for the Adds and Deletes delta tables used in versioning, which is why edits are not visible.
2. Why Alter the View to Use a Versioned View?
* By modifying the standard database view to reference the versioned view, the published web layer will reflect changes made in the Default version, including ongoing edits.
* This ensures that updates to the points feature class are visible in the web layer without requiring manual intervention.
3. Why Not Other Options?
* Have All Editors Reconcile and Post Points Edits to Default:
* While this ensures edits are moved to the Default version, it requires continuous manual reconciliation and posting, which is impractical for a frequently edited dataset.
* Rebuild Indexes and Calculate Database Statistics on Points:
* These actions improve query performance but do not address the core issue of the standard view not reflecting versioned edits.
Steps to Alter the View:
* Identify the versioned view associated with the points feature class. It typically has a name like points_EVW.
* Modify the SQL for the existing view to reference the versioned view:
CREATE OR REPLACE VIEW points_web AS
SELECT <fields> FROM points_EVW;
* Update the web layer to use the modified view as the data source.
* Test the web layer to confirm that edits made to the Default version are now visible.
References from Esri Documentation and Learning Resources:
* Versioned Views in Enterprise Geodatabases
* Publishing Data from Views
Conclusion:
To ensure edits made to the points feature class are visible in the web layer, thedatabase view should be altered to reference the versioned view, which accounts for edits in the Default version.

NEW QUESTION # 48
A GIS administrator is investigating reports of slow performance in a map of complex polygons. The investigation finds the following:
* The feature class is in an enterprise geodatabase
* This data has been published as a map service in ArcGIS Enterprise
* The feature class is not versioned
* The map seems to perform slowly at several zoomed-out extents in the map
* Queries on the attributes perform quickly
Which recommendation should the GIS administrator make?

A. Show cached data for the zoomed extents
B. Compress the enterprise geodatabase
C. Run the Analyze Datasets tool

Answer: A

Explanation:
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.

NEW QUESTION # 49
......

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