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Non-functional testing focuses on how a system operates and meets user expectations in terms of qualities like:

Performance: Response times, load handling, scalability

Usability: Ease of use, user interface design

Security: Protection against unauthorized access and data breaches

Reliability: System stability and availability

Maintainability: Ease of making changes and updates

Why not the other options?

A . Specific behaviors and outputs of the system: This is the focus of functional testing, which verifies that the system does what it's supposed to do.

C . The creation of records and setting field values: This is a specific functional aspect of the system.

D . Functional requirements outlined in the design document: These are tested during functional testing.

The Foundation stage of the CSDM framework focuses primarily on establishing the core structure of your CMDB. This involves:

Defining the scope: Determine which services and applications will be managed within the CMDB.

Building the foundation data model: Implement the core CSDM classes and their relationships. This includes key classes like Application Service, Business Application, and Technical Service Offering.

Populating foundational data: Start populating the CMDB with basic information about your core services, applications, and the technologies that support them.

Why not the other options?

A: While network infrastructure CIs are important, they are not the primary focus in the Foundation stage. The focus is on the core service and application model.

B: Accurate business information is crucial for reporting, but the Foundation stage prioritizes establishing the structural relationships within the CMDB.

D: Working with ITSM tables is part of the broader CMDB implementation, but the Foundation stage focuses on the core CSDM classes, which extend beyond ITSM.

Key considerations for data integrations in ServiceNow include:

B . Accessing and using only authorized data: Ensure that integrations only access and use data that is authorized and necessary for the integration's purpose. This is crucial for data security and privacy.

C . Fetching only clean and accurate data: Data quality is essential for successful integrations. Implement data validation and cleansing processes to ensure that only accurate and consistent data is transferred.

E . Maintaining a single source of truth: Whenever possible, identify a single authoritative source for each data element to avoid inconsistencies and conflicts.

Why not the other options?

A . Duplicating data across all systems: This can lead to data inconsistencies and increased storage costs.

D . Maximizing data transfer volume: The focus should be on transferring the necessary data efficiently, not maximizing volume.

Usability testing is the type of testing that relies on human observation to assess the user-friendliness of a software product.

In usability testing:

Real users interact with the software or product in a realistic setting.

Observers watch and record user behavior, noting any difficulties, frustrations, or areas of confusion.

Feedback is gathered from users to understand their experiences and identify areas for improvement.

Why not the other options?

A . Smoke testing: A quick, preliminary test to ensure basic functionality is working.

C . Integration testing: Tests the interaction between different modules or components of a system.

D . System testing: Tests the entire system as a whole.

Effective error handling is crucial for maintaining the reliability and stability of ServiceNow integrations. Recommended strategies include:

B . Establish a process to review and monitor errors: Regularly review integration logs and error reports to identify trends, potential issues, and areas for improvement.

C . Classify errors into specific categories: Categorizing errors (e.g., data errors, connection errors, authorization errors) helps with troubleshooting and identifying root causes.

E . Log all errors to a centralized location: Maintain a centralized log of all integration errors for analysis and troubleshooting. This provides a comprehensive view of integration health.

Why not the other options?

A . Ignore minor errors to reduce system load: Ignoring errors can lead to data inconsistencies and integration failures. All errors should be addressed appropriately.

D . Create email notifications for all integration errors: While notifications can be useful for critical errors, sending emails for all errors can lead to alert fatigue and may not be the most efficient way to manage errors.