Salesforce Data-Architect exam dumps - Salesforce Certified Data Architect

  • Exam Code: Data-Architect
  • Exam Name: Salesforce Certified Data Architect
  • Updated: Aug 18, 2026     Q & A: 260 Questions and Answers

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To become a Salesforce Certified Data Architect, candidates must pass the certification exam. Data-Architect exam consists of multiple-choice questions and is administered online. Data-Architect exam is designed to test candidates on their knowledge of Salesforce data architecture and their ability to apply that knowledge to real-world scenarios.

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To be eligible for the Salesforce Data-Architect certification exam, candidates must have a deep understanding of Salesforce data architecture and must have a minimum of five years of experience in designing and implementing data solutions for Salesforce. Data-Architect exam is divided into two parts – a multiple-choice exam and a hands-on scenario-based exam. The multiple-choice exam tests the candidates' knowledge of Salesforce data architecture concepts, while the hands-on scenario-based exam tests their ability to design and implement data solutions in a real-world scenario. Overall, the Salesforce Data-Architect certification exam is a highly sought-after certification, and it can help professionals advance their careers in the Salesforce ecosystem.

Salesforce Data-Architect certification exam is designed to test the candidate's ability to design, implement, and maintain complex data architectures that are scalable, reliable, and secure. Data-Architect exam covers a wide range of topics, including data modeling, data integration, data governance, and data security. Data-Architect exam is designed to be challenging, and candidates must have a deep understanding of the Salesforce platform and its underlying technologies.

Reference: https://trailheadacademy.salesforce.com/certificate/exam-data-architect---Plat-Arch-201

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Salesforce Data-Architect Exam Syllabus Topics:

SectionObjectives
Topic 1: Master Data Management (MDM)- MDM architecture
  • 1. Data synchronization approaches
    • 2. Golden record design
      Topic 2: Large Data Volume and Performance- Scalability considerations
      • 1. Bulk data processing strategies
        • 2. Indexing and query optimization
          Topic 3: Data Integration- Salesforce integration tools
          • 1. Platform events and change data capture
            • 2. MuleSoft and REST/SOAP APIs
              - Integration patterns
              • 1. API-based integration strategies
                • 2. ETL vs real-time integration
                  Topic 4: Data Governance and Management- Data quality management
                  • 1. Deduplication strategies
                    • 2. Data validation rules
                      - Security and compliance
                      • 1. Data access controls
                        • 2. Regulatory compliance considerations
                          Topic 5: Data Modeling and Database Design- Salesforce data model design
                          • 1. Schema design for scalability
                            • 2. Standard and custom objects usage
                              - Data modeling concepts
                              • 1. Normalization and denormalization strategies
                                • 2. Relational vs. non-relational data design

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