Given a Customer Scenario, Recommend Appropriate Techniques and Methods for Ensuring High Data Quality at the Point of Entry, Such as Client/server Side Validation Rules, Workflows, Approvals, Data.com Clean, Duplicate Prevention. DATA-ARCHITECT Practice Questions (Page 3)

Questions 11–15

1. 11foundation · easy

   Which data quality improvement is Data.com Clean specifically designed to provide?

   • AAutomatically merging duplicate records
   • BRequiring a manager to approve new accounts
   • CBlocking records with missing phone numbers from being saved
   • DEnriching contact records with additional information such as job title and company details
   Reveal Solution Discussion Select an answer first
2. 12foundation · easy

   How do matching rules support duplicate prevention?

   • AThey standardize address data to prevent duplicates
   • BThey automatically delete duplicate records
   • CThey require a manager to approve each new record
   • DThey define the criteria used to identify records that are likely duplicates
   Reveal Solution Discussion Select an answer first
4. 13application · medium

   A nonprofit uses Salesforce to track donations. Staff enter donations through a custom Lightning component, and occasionally they enter a donation amount of $0 or negative values. The admin wants to prevent this at the point of entry, but also wants to ensure the rule applies if data is imported via Data Loader. What should the admin do?

   • ACreate a validation rule on the donation amount field that requires it to be greater than zero.
   • BUse a workflow rule to update the donation amount to $1 if it is $0 or negative.
   • CCreate an approval process for any donation under $10.
   • DAdd a client-side check in the Lightning component to block $0 or negative amounts.
   Reveal Solution Discussion Select an answer first
5. 14foundation · easy

   In an approval process, what happens when a record is submitted for approval?

   • AThe record is deleted if it does not meet quality standards
   • BThe record is automatically corrected based on predefined rules
   • CThe record is immediately saved and made visible to all users
   • DThe record is locked and routed to an approver for review
   Reveal Solution Discussion Select an answer first
6. 15foundation · easy

   What is the primary purpose of Data.com Clean?

   • ATo standardize, enrich, and validate account and contact data
   • BTo enforce validation rules on data entered through the API
   • CTo automatically create duplicate records for testing
   • DTo require human approval before records are saved
   Reveal Solution Discussion Select an answer first