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SalesforceCertified Data Architect

Domain 2Objective 2

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 6)

Part of the CONCEPTUAL DESIGN domain, which accounts for 15% of the DATA-ARCHITECT exam.

30questions here
6free pages
10concepts
15%of the exam

Questions 26–30

  1. 26foundation · easy

    A customer wants to ensure that users select valid combinations of Country and State on Contact records. Which approach is most appropriate?

    Select an answer first
  2. 27foundation · easy

    Which scenario is best addressed by a validation rule?

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  3. 28foundation · easy

    What is the primary purpose of a validation rule in Salesforce?

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  4. 29foundation · easy

    In a dependent picklist, what is the field that determines the available values in another picklist called?

    Select an answer first
  5. 30foundation · easy

    What is the primary purpose of a matching strategy in data quality management?

    Select an answer first
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