Given a Customer Scenario, Recommend Approaches for Improving Data Quality Along Key Dimensions (e.g., Data Duplication, Completeness, Accuracy, Integrity Etc.) Using Various Techniques (e.g., Data Assessment/profiling, Cleansing, Standardization/normalization, Matching & Merging, Declarative Components) in Salesforce (e.g., Validation Rules, Visual Indicators, Dependent Pick Lists, Etc.). DATA-ARCHITECT Practice Questions (Page 4)

Questions 16–20

1. 16foundation · easy

   Which Salesforce declarative component can be used to prevent users from entering an invalid value at data entry?

   • AReport
   • BVisual indicator
   • CDependent picklist
   • DValidation rule
   Reveal Solution Discussion Select an answer first
2. 17foundation · easy

   When merging two duplicate account records in Salesforce, what should be done to preserve data integrity?

   • ADelete both records and create a new one from scratch
   • BAlways keep the oldest record and delete the newer one
   • CConsolidate fields, keeping the most complete and accurate values
   • DKeep both records but change their names
   Reveal Solution Discussion Select an answer first
4. 18foundation · easy

   A customer has a high number of duplicate Account records. Which approach is most appropriate to address this data quality issue?

   • AStandardize the Account Name format
   • BCreate a validation rule to require a unique Account Name
   • CUse a visual indicator to highlight duplicates
   • DUse matching rules and duplicate rules to identify and merge duplicates
   Reveal Solution Discussion Select an answer first
5. 19foundation · easy

   Which Salesforce feature is commonly used to implement a visual indicator that changes color based on a field value?

   • AWorkflow rule
   • BFormula field with a color rule
   • CValidation rule
   • DDependent picklist
   Reveal Solution Discussion Select an answer first
6. 20application · medium

   A retail company has a large number of Contact records with missing phone numbers and some with invalid email formats. The data architect wants to improve the completeness and accuracy of this data. Which approach should the architect recommend?

   • AUse a workflow rule to automatically populate missing phone numbers from the Account's phone number.
   • BCreate a validation rule that requires all Contact records to have a phone number and a valid email format.
   • CDelete all Contact records that have missing phone numbers or invalid emails to improve data quality.
   • DRun a data profiling report to identify the percentage of missing phone numbers and invalid emails, then use a data cleansing tool to correct or fill in the data where possible.
   Reveal Solution Discussion Select an answer first