Universal Containers (UC) has several custom Visualforce applications have been developed in which users are able to edit Opportunity records. UC struggles with data completeness on their Opportunity records and has decided to make certain fields required that have not been in the past. The newly required fields are dependent on the Stage of the Opportunity, such that certain fields are only required once an Opportunity advances to later stages. There are two fields. What is the simplest approach to handle this new requirement?

• A. Update these Opportunity field definitions in Setup to be required.
• B. Update the Opportunity page layout to mark these fields as required.
• C. Write an Apex trigger that checks each field when records are saved.
• D. Use a validation rule for each field that takes the Stage into consideration.

Universal Containers (UC) has a complex system landscape and is implementing a data governance program for the first time Which two first steps would be appropriate for UC to initiate an assessment of data architecture? Choose 2 answers

• A. Engage with business units and IT to assess current operational systems and data models.
• B. Engage with executive sponsorship to assess enterprise data strategy and goals.
• C. Engage with database administrators to assess current database performance metrics.
• D. Engage with IT program managers to assess current velocity of projects in the pipeline.

Universal container (UC) would like to build a Human resources application on Salesforce to manage employee details, payroll, and hiring efforts. To adequately and store the relevant data, the application will need to leverage 45 custom objects. In addition to this, UC expects roughly 20,00 API calls into Salesfoce from an n-premises application daily.
Which license type should a data architect recommend that best fits these requirements?

• A. Service Cloud
• B. Lightning Platform plus
• C. Lightning platform Start
• D. Lightning External Apps Starts

Northern Trail Outfitters < NTO > is streaming IoT data from connected devices to a cloud database. Every
24 hours. 100,000 records are generated.
NIO employees will need to see these lol records within Salesforce and generate weekly reports on it.
Developers may also need to write programmatic logic to aggregate the records and incorporate them into workflows.
Which data pattern will allow a data architect to satisfy these requirements, while also keeping limits in mind?

• A. Persistence
• B. Bidirectional integration
• C. Virtualization
• D. Unidirectional integration

To address different compliance requirements, such as general data protection regulation (GDPR), personally identifiable information (PII), of health insurance Portability and Accountability Act (HIPPA) and others, a SF customer decided to categorize each data element in SF with the following:
* Data owner
* Security Level, such as confidential
* Compliance types such as GDPR, PII, HIPPA
A compliance audit would require SF admins to generate reports to manage compliance.
What should a data architect recommend to address this requirement?

• A. Use field metadata attributes for compliance categorization, data owner, and data sensitivity level.
• B. Use metadata API, to extract field attribute information and use the extract to classify and build reports
• C. Build reports for field information, then export the information to classify and report for Audits.
• D. Create a custom object and field to capture necessary compliance information and build custom reports.