Given a Customer Scenario, Recommend Appropriate Approaches and Techniques to Capture and Maintain Customer Metadata to Preserve Traceability and Establish a Common Context for Business Rules (e.g., Applying Weights to Attributes Used in Matching Process by Their Importance, Data Classification, Global/local Attributes, Field Audit Trails, Etc.). DATA-ARCHITECT Practice Questions (Page 3)

Questions 11–15

1. 11expert · hard

   A data architect is building a customer matching solution in Data Cloud. The matching rule uses a weighted combination of email, phone, and last name. The business has a requirement that any change to the matching weights must be traceable to a specific change request. The architect wants to use custom metadata to store the weights. What additional step is necessary to fully satisfy the traceability requirement?

   • AEnable the 'Track Field History' setting on the custom metadata type's weight fields.
   • BCreate a new version of the custom metadata type record each time the weights change and keep the old versions in a separate custom object.
   • CRely on the Setup Audit Trail to capture who changed the custom metadata type record.
   • DStore the change request ID in a custom field on the custom metadata type record and update it whenever the weights are changed.
   Reveal Solution Discussion Select an answer first
2. 12expert · hard

   A company has a matching rule in Data Cloud that uses weights stored in a custom metadata type. The weights were last reviewed six months ago. The business has since launched a new product line, and the data architect suspects that the relative importance of the 'Email' attribute has increased. The architect wants to ensure the weights are still optimal. What is the most appropriate action?

   • ASchedule a review meeting with business stakeholders to discuss whether the current weights still reflect the business priorities, and update the custom metadata type if needed.
   • BCreate a new custom metadata type with the new weights and switch the matching rule to use it.
   • CLeave the weights unchanged until a data quality issue is detected.
   • DAutomatically increase the weight of the 'Email' attribute based on the new product launch.
   Reveal Solution Discussion Select an answer first
4. 13application · medium

   A data architect is configuring a matching rule in Data Cloud for a B2C company. The rule uses first name, last name, email, and phone. The architect wants to assign weights based on the uniqueness and reliability of each attribute. Email is generally unique and reliable, phone is fairly reliable but can be shared, and first/last names are not unique. What is the most appropriate weighting?

   • AEmail: 40, Phone: 40, Last Name: 10, First Name: 10
   • BEmail: 25, Phone: 25, Last Name: 25, First Name: 25
   • CEmail: 10, Phone: 20, Last Name: 30, First Name: 40
   • DEmail: 50, Phone: 30, Last Name: 15, First Name: 5
   Reveal Solution Discussion Select an answer first
5. 14foundation · easy

   Which approach helps establish a shared context for business rules across an organization?

   • AUsing technical field names only, without business descriptions
   • BCreating a central metadata glossary with approved definitions and aliases
   • CAllowing each team to maintain its own metadata documentation independently
   • DStoring metadata in a format that is only accessible to data architects
   Reveal Solution Discussion Select an answer first
6. 15foundation · easy

   What is a key benefit of establishing a periodic review process for customer metadata?

   • AIt ensures metadata remains aligned with evolving business definitions and source system changes
   • BIt eliminates the need for automated metadata capture tools
   • CIt guarantees that metadata will never become outdated
   • DIt automatically updates all metadata without human intervention
   Reveal Solution Discussion Select an answer first