Esri Certification EGMP2201 Updated Exam

 Understanding the Scenario:

The request involves creating a view that dynamically combines data from aversioned feature classand anonspatial table.

The data needs to be from achild versionand updated dynamically.

 Key Considerations:

Versioned Feature Class:Standard feature classes in versioned geodatabases store edits in delta tables (adds and deletes). Accessing data from a specific version requires using theversioned view, which includes these edits.

Dynamic Updates:Views created on the versioned view ensure that the data reflects the most current version edits.

 Steps to Create the View:

Identify the versioned view for the feature class (created automatically during versioning).

Create a SQL query to join the versioned view and the nonspatial table on the appropriate key(s).

Save the SQL query as a database view.

 References:

Esri Documentation: Versioned Views.

Creating Views with Versioned Data: Guidelines for joining versioned views with other tables in SQL.

 Why the Correct Answer is C:Using the versioned view ensures that data reflects edits from the specified child version. Joining this view with the nonspatial table meets the requirement for dynamic updates. Options A and B would not provide data from the versioned child version dynamically.

Comprehensive Detailed Step-by-Step Explanation with All Enterprise Geodata References:

AnEnterprise geodatabaseis the most appropriate choice for this scenario due to the following reasons:

1. Requirement to Store Data Locally on Organization's Servers

AnEnterprise geodatabaseallows organizations to store GIS data locally in their own database management systems (DBMS), such as PostgreSQL, SQL Server, or Oracle.

This meets the requirement of maintaining control over data storage and ensuring the data resides within the organization's infrastructure.

2. Editing GIS Data via Web Services

Enterprise geodatabases seamlessly integrate with ArcGIS Server, enabling data editing via web services.

Organizations can publish feature services to allow authorized users to edit GIS data in real-time or in a disconnected environment (via sync).

These services support advanced editing workflows, including versioning and conflict resolution.

3. Indexing Specific Business Fields for Performance

Enterprise geodatabases offer robust indexing options to enhance query and editing performance.

You can:

Create attribute indexeson fields that are frequently queried.

Usespatial indexesto improve the speed of spatial queries.

This level of customization helps meet the performance demands of specific business workflows.

4. Advantages Over Other Storage Options

File Geodatabase:

While it is suitable for smaller datasets and local storage, it does not support multi-user editing, integration with web services, or advanced indexing for business fields.

Hosted Relational Database:

This option is part of ArcGIS Online or ArcGIS Enterprise managed services and stores data in the cloud, which contradicts the requirement for local storage.

It also does not provide the same level of control or indexing capabilities as an enterprise geodatabase.

References from Esri Documentation and Learning Resources:

Enterprise Geodatabases—ArcGIS Pro Documentation

Configuring Indexes in Geodatabases

Publishing Feature Services for Editing

Conclusion:

AnEnterprise geodatabasenot only meets all the stated requirements (local storage, web service editing, and indexed fields for performance) but also provides additional scalability, security, and multi-user editing capabilities.

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.