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Salesforce Certified Data Architect Sample Questions (Q32-Q37):
NEW QUESTION # 32
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. Create a custom object and field to capture necessary compliance information and build custom reports.
- C. Build reports for field information, then export the information to classify and report for Audits.
- D. Use metadata API, to extract field attribute information and use the extract to classify and build reports
Answer: A
Explanation:
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.
NEW QUESTION # 33
Universal Container (UC) has accumulated data over years and has never deleted data from its Salesforce org. UC is now exceeding the storage allocations in the org. UC is now looking for option to delete unused from the org.
Which three recommendations should a data architect make is order to reduce the number of records from the org?
Choose 3 answers
- A. Use hard delete in Bulk API to permanently delete records from Salesforce.
- B. Use hard delete in batch Apex to permanently delete records from Salesforce.
- C. Archive the records in enterprise data warehouse (EDW) before deleting from Salesforce.
- D. Use Rest API to permanently delete records from the Salesforce org.
- E. Identify records in objects that have not been modified or used In last 3 years.
Answer: A,C,E
Explanation:
Using hard delete in Bulk API, identifying records that have not been modified or used in last 3 years, and archiving the records in EDW before deleting from Salesforce are all good recommendations to reduce the number of records from the org1. Using hard delete in batch Apex or Rest API may not be as efficient or scalable as Bulk API
NEW QUESTION # 34
Universal Containers (UC) is migrating data from legacy system to Salesforce. During data analysis it was discovered that data types of fields being migrated do not match with Salesforce data types.
Which solution should a data architect use to ensure successful data migrations?
- A. Migrate legacy data to a staging database for mapping then leverage an ETL tool to transform the data and load into Salesforce.
- B. Export legacy data into the staging database and leverage stored procedures to transform data types before loading into Salesforce.
- C. Migrate the legacy data leveraging an ETL tool to transform data types and load data into Salesforce.
- D. Export legacy data into CSV files and leverage data loader to load data into Salesforce.
Answer: C
Explanation:
According to this article, migrating the legacy data leveraging an ETL tool to transform data types and load data into Salesforce can be a way to ensure successful data migrations. The article states that ETL tools can help with data cleansing, mapping, transformation, and loading, and that they can handle different data types and formats. The article also provides some best practices for data migration, such as identifying the data to migrate, creating templates for the data, preparing the destination org, and validating the data.
NEW QUESTION # 35
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 the Opportunity page layout to mark these fields as required.
- B. Use a validation rule for each field that takes the Stage into consideration.
- C. Update these Opportunity field definitions in Setup to be required.
- D. Write an Apex trigger that checks each field when records are saved.
Answer: B
NEW QUESTION # 36
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. Create a custom object and field to capture necessary compliance information and build custom reports.
- C. Build reports for field information, then export the information to classify and report for Audits.
- D. Use metadata API, to extract field attribute information and use the extract to classify and build reports
Answer: A
Explanation:
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.
NEW QUESTION # 37
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