Salesforce Updated Data-Architect Exam Questions and Answers by carmen

 Engaging with executive sponsorship to assess enterprise data strategy and goals, and engaging with business units and IT to assess current operational systems and data models are two first steps that would be appropriate for UC to initiate an assessment of data architecture. These steps will help to understand the current state of data management, the business needs and expectations, and the gaps and opportunities for improvement. Engaging with IT program managers to assess current velocity of projects in the pipeline, and engaging with database administrators to assess current database performance metrics are not relevant steps for assessing data architecture, as they are more related to project management and technical performance.

The data architect should recommend using field metadata attributes for compliance categorization, data owner, and data sensitivity level. This will allow the SF admins to generate reports to manage compliance based on the field metadata attributes that are defined for each data element in SF. Option A is incorrect because using metadata API to extract field attribute information and use the extract to classify and build reports will require additional development effort and may not be up-to-date with the latest changes in SF. Option C is incorrect because creating a custom object and field to capture necessary compliance information and build custom reports will require additional configuration effort and may not be consistent with the actual data elements in SF. Option D is incorrect because building reports for field information, then exporting the information to classify and report for audits will require additional manual effort and may not be accurate or timely.

 Option C is the best answer because reviewing projected data storage needs is an important step in designing a field-level audit and recovery plan1. You need to estimate how much data storage you will need in the future and plan accordingly. Option A is not correct because reducing data storage by purging old data may not be sufficient or desirable for backup purposes. Option B is not correct because implementing an AppExchange package may not be customized or compatible with your org’s requirements. Option D is not correct because scheduling a weekly export file may not be frequent or granular enough for field-level audit and recovery.

Persistence is the data pattern that will allow a data architect to satisfy the requirements, while also keeping limits in mind. Persistence means storing data from external sources in Salesforce objects, either standard or custom. This allows you to access the data within Salesforce and use it for reporting, analytics, workflows, and other features. Persistence also helps you avoid hitting API limits or performance issues when accessing large volumes of data from external systems. You can use various tools such as Data Loader, Bulk API, or Platform Events to persist IoT data from connected devices to a cloud database in Salesforce.