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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.

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Salesforce Data-Architect (Salesforce Certified Data Architect) Exam is a highly sought-after certification for professionals working in the Salesforce ecosystem. Data-Architect exam is designed to test a candidate's knowledge and expertise in designing and implementing complex data solutions on the Salesforce platform. Salesforce Certified Data Architect certification emphasizes the importance of data modelling, data governance, data integration, and data migration in Salesforce.

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

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Salesforce Data-Architect Exam Syllabus Topics:

SectionWeightObjectives
Data Governance and Compliance20%- Data lifecycle management
  • 1. Data privacy and security
  • 2. Data classification and handling
  • 3. Data retention and archiving policies
- Data governance framework
  • 1. Data stewardship and ownership
  • 2. Compliance and regulatory requirements
  • 3. Data quality standards
Data Modeling and Database Design25%- Indexing and data structure
  • 1. Skinny tables and big objects
  • 2. Standard and custom indexes
  • 3. Query optimization strategies
- Design scalable data models
  • 1. Object relationships and cardinality
  • 2. Data model optimization for performance
  • 3. Custom and standard object design
Large Data Volume Considerations20%- Performance and scalability
  • 1. Avoiding and resolving data skew
  • 2. Governor limits and bulk processing
  • 3. Handling millions of records
- Storage and optimization
  • 1. Archiving and off-platform storage
  • 2. Performance tuning techniques
  • 3. Storage limits and management
Data Integration and Master Data Management10%- Integration patterns and tools
  • 1. External data sources and objects
  • 2. Real-time vs batch integration
  • 3. REST, SOAP, and Bulk API usage
- Master data management
  • 1. Data synchronization and consistency
  • 2. MDM strategy and implementation
  • 3. Single source of truth design
Salesforce Data Management25%- Data import and export strategies
  • 1. Migration planning and execution
  • 2. Tools: Data Loader, Import Wizard, Bulk API
  • 3. Data validation and cleansing
- Sharing and visibility design
  • 1. Sharing rules, manual sharing, Apex sharing
  • 2. Organization-wide defaults, role hierarchy
  • 3. Data access and security model

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