Salesforce Certified Data Architect Practice Test
Build your confidence for Salesforce Certified Data Architect. Practice the concepts, understand the answers, and strengthen your knowledge one question at a time.
Try a sample questionExam overview and details
The Salesforce Certified Data Architect credential validates an architect's expertise in designing scalable, secure, and high-performance data solutions on the Salesforce Customer 360 platform. This advanced certification demonstrates mastery across the entire data lifecycle, from strategic governance and modeling to complex migration, integration, and management of large data volumes (LDV). Certified professionals are equipped to translate complex business requirements into robust technical architectures that ensure data integrity, quality, and accessibility. Earning this certification signifies a deep understanding of how to leverage Salesforce's data model, declarative features, and APIs to build sustainable systems that support enterprise-scale operations and drive data-informed decision-making. It is a critical credential for architects responsible for the foundational data strategy that underpins all CRM initiatives and digital transformations.
Sample Questions
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Pioneer Health merged two Salesforce orgs. Both have an Account Type field, but one uses it for market segment and the other for customer lifecycle stage. What should the architect do before migration?
AW Computing wants to report on 4 billion immutable clickstream events linked to Campaigns. Users need aggregate trends, not transactional updates in Salesforce. Which pattern best fits Salesforce platform constraints?
Pioneer Health wants to measure whether Account data quality is improving after introducing stewardship queues. Which KPI set best supports governance?
Ursa Major Solar has a private sharing model and plans to load 5 million child records under 40,000 Accounts before go-live. Sharing rules are still being tuned. Which LDV tactic should be considered during the load?
Northern Trail Outfitters wants a stewardship operating model for duplicate review. Data stewards are overloaded and want automation, but legal requires human review for strategic accounts. Which approach is best?
Career Opportunities & Salary
Exam insights and study advice
Achieving the Salesforce Certified Data Architect certification is a definitive career milestone that establishes you as a strategic leader in the Salesforce ecosystem. It provides industry-wide recognition of your ability to solve the most complex data challenges, making you a sought-after expert for high-impact roles. This credential directly correlates with career advancement into senior architect, principal consultant, and technical leadership positions, often commanding a significant premium in compensation. For organizations, it serves as a trusted validation of an individual's capability to design data architectures that mitigate risk, reduce technical debt, and maximize the long-term value of their Salesforce investment.
What this exam covers
Use the published domain weights to plan your study. Practice results do not predict your certification exam score.
01Data Modeling/Database Design
Topics
- Compare and contrast various techniques and considerations for designing a data model for the Customer 360 Platform.
- Given a scenario, recommend approaches and techniques to design a scalable data model that obeys the current security and sharing model.
- Compare and contrast various techniques, approaches and considerations for capturing and managing business and technical metadata.
- Compare and contrast the different reasons for implementing big objects versus standard/custom objects within a production instance.
- Given a customer scenario, recommend approaches and techniques to avoid data skew.
Learning objectives
- Compare and contrast various techniques and considerations for designing a data model for the Customer 360 Platform.: (for example, objects, fields & relationships, object features)
- Given a scenario, recommend approaches and techniques to design a scalable data model that obeys the current security and sharing model.
- Compare and contrast various techniques, approaches and considerations for capturing and managing business and technical metadata.: (for example, business dictionary, data lineage, taxonomy, data classification)
- Compare and contrast the different reasons for implementing big objects versus standard/custom objects within a production instance.: alongside the unique pros and cons of utilizing big objects in a Salesforce data model
- Given a customer scenario, recommend approaches and techniques to avoid data skew.: (record locking, sharing calculation issues, and excessive child to parent relationships)
02Salesforce Data Management
Topics
- Given a customer scenario, recommend appropriate combination of Salesforce license types to effectively leverage standard and custom objects to meet business needs.
- Given a customer scenario, recommend techniques to ensure data is persisted in a consistent manner.
- Given a scenario with multiple systems of interaction, describe techniques to represent a single view of the customer on the Salesforce Platform.
- Given a customer scenario, recommend a design to effectively consolidate and/or leverage data from multiple Salesforce instances.
Learning objectives
- Given a customer scenario, recommend appropriate combination of Salesforce license types to effectively leverage standard and custom objects to meet business needs.
- Given a customer scenario, recommend techniques to ensure data is persisted in a consistent manner.
- Given a scenario with multiple systems of interaction, describe techniques to represent a single view of the customer on the Salesforce Platform.
- Given a customer scenario, recommend a design to effectively consolidate and/or leverage data from multiple Salesforce instances.
03Large Data Volume Considerations
Topics
- Given a customer scenario, design a data model that scales considering LDV and solution performance.
- Given a customer scenario, recommend a data archiving and purging plan that is optimal for the customer's data storage management needs.
- Given a customer scenario, decide when to use virtualized data and describe virtualized data options.
Learning objectives
- Given a customer scenario, design a data model that scales considering LDV and solution performance.
- Given a customer scenario, recommend a data archiving and purging plan that is optimal for the customer's data storage management needs.
- Given a customer scenario, decide when to use virtualized data and describe virtualized data options.
04Data Migration
Topics
- Given a customer scenario, recommend appropriate techniques and methods for ensuring high data quality at load time.
- Compare and contrast various techniques for improving performance when migrating LDVs into Salesforce.
- Compare and contrast various techniques and considerations for exporting data from Salesforce.
Learning objectives
- Given a customer scenario, recommend appropriate techniques and methods for ensuring high data quality at load time.
- Compare and contrast various techniques for improving performance when migrating LDVs into Salesforce.
- Compare and contrast various techniques and considerations for exporting data from Salesforce.
05Data Governance
Topics
- Given a customer scenario, recommend an approach for designing a General Data Protection Regulation (GDPR) compliant data model.
- Compare and contrast various approaches and considerations for designing and implementing an enterprise data governance program.
Learning objectives
- Given a customer scenario, recommend an approach for designing a General Data Protection Regulation (GDPR) compliant data model.: Discuss the various options to identify, classify, and protect personal and sensitive information
- Compare and contrast various approaches and considerations for designing and implementing an enterprise data governance program.
06Master Data Management
Topics
- Compare and contrast the various techniques, approaches and considerations for implementing master data management (MDM) Solutions.
- Given a customer scenario, recommend and use techniques for establishing a 'golden record' or 'system of truth' for the customer domain in a single org.
- Given a customer scenario, recommend approaches and techniques for consolidating data attributes from multiple sources.
- Given a customer scenario, recommend appropriate approaches and techniques to capture and maintain customer reference and metadata.
Learning objectives
- Compare and contrast the various techniques, approaches and considerations for implementing master data management (MDM) Solutions.: (for example, MDM implementation styles; harmonizing and consolidating data from multiple sources; establishing data survivorship rules, thresholds and weights; leveraging external reference data for enrichment; canonical modeling techniques, hierarchy management)
- Given a customer scenario, recommend and use techniques for establishing a 'golden record' or 'system of truth' for the customer domain in a single org.
- Given a customer scenario, recommend approaches and techniques for consolidating data attributes from multiple sources.: Discuss criteria and methodology for picking the winning attributes
- Given a customer scenario, recommend appropriate approaches and techniques to capture and maintain customer reference and metadata.: preserve traceability and establish a common context for business rules