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Salesforce Certified Data Architect certification is highly regarded in the industry and is recognized by employers worldwide. It demonstrates an individual's expertise in designing and implementing complex data solutions using Salesforce. It is also an excellent way to advance one's career in the Salesforce ecosystem and increase job opportunities.
Reference: https://trailheadacademy.salesforce.com/certificate/exam-data-architect---Plat-Arch-201
Salesforce Data-Architect certification is a highly sought-after certification in the Salesforce ecosystem, and it offers numerous benefits for professionals looking to advance their careers in the field of data management and analytics. Salesforce Certified Data Architect certification validates the expertise and knowledge of the certified professionals, and it can lead to new career opportunities and growth in the Salesforce ecosystem. The Salesforce Certified Data-Architect exam is a challenging exam that requires in-depth knowledge of the Salesforce platform, and it is an excellent opportunity for professionals to showcase their skills and expertise.
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Salesforce Data-Architect Exam Syllabus Topics:
| Section | Weight | Objectives |
| Data Modeling | 25% | - Large Data Volumes (LDV) design considerations
- Big Objects and external objects
- Skinny tables for performance optimization
- Indexing strategies
- Normalization and denormalization strategies
|
| Data Integration | 15% | - Sharing rules impact on data integration
- API-based integration (REST, SOAP, Bulk API)
- ETL tools and data migration strategies
- Handling locks and parallelism during migration
- Real-time vs batch integration patterns
|
| Data Governance | 20% | - Compliance and regulatory considerations
- Data quality standards and metrics
- Data retention and archiving policies
- Data stewardship roles and responsibilities
|
| Master Data Management | 20% | - Data duplication and matching rules
- Data cleansing techniques
- Identity resolution
|
| Data Architecture | 20% | - Governor limits and bulk processing
- Performance tuning and optimization
- Archiving and data lifecycle management
- Architecture patterns and design principles
|