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Salesforce Certified Platform Data Architect Exam Prep

Master Salesforce Platform Data Architect! New course covers the latest exam questions and Salesforce release. Get certified.

17students
0
Certificate
ForceWise EnvironmentTM
ForceWise EnvironmentTMForceWiseTM Team

Course Content

Salesforce Certified Platform Data Architect Exam Prep is an intermediate-level Udemy course taught by ForceWise EnvironmentTM. It is taught in English and includes a certificate of completion. 17 students have enrolled. It is a paid course, last updated August 2025.

Become a Salesforce Certified Platform Data Architect: Design Scalable Data Solutions

The Salesforce Certified Platform Data Architect certification validates your expertise in crafting robust, high-performing data solutions on the Salesforce Customer 360 Platform. This sought-after credential demonstrates your ability to analyze complex architecture requirements, expertly manage large data volumes, and deliver secure, reliable, and top-quality data solutions. If you're a data professional looking to advance your career in the Salesforce ecosystem, this certification is a significant step.

Who Should Pursue This Certification?

This certification is ideal for experienced professionals who design and manage intricate Salesforce data solutions. Typical candidates possess:

  • 2-3 years of Salesforce experience
  • 5+ years working with data-driven solutions

Common roles include:

  • Salesforce Data Architect
  • Solution Architect / Technical Architect
  • Advanced Administrator
  • Advanced Platform Developer

Skills Assessed: Key Knowledge Areas

The exam assesses your proficiency in these critical areas:

  • Data Modeling & Database Design (25%): Master techniques for designing scalable data models for the Customer 360 Platform. Understand object relationships, fields, and object features. Learn to recommend approaches that align with Salesforce's security and sharing model. Compare and contrast metadata management techniques (business dictionaries, data lineage, taxonomy). Evaluate the pros and cons of using Big Objects versus standard/custom objects. Address data skew issues (record locking, sharing, child-parent relationships).
  • Master Data Management (MDM) (5%): Explore various MDM implementation styles, data harmonization, and data consolidation strategies. Learn to establish a "golden record" for customer data. Understand how to capture and maintain customer reference data for traceability and context.
  • Salesforce Data Management (25%): Recommend appropriate Salesforce license types for optimal data utilization. Ensure data consistency across systems. Design solutions to create a single customer view across multiple systems. Strategically consolidate data from multiple Salesforce instances.
  • Data Governance (10%): Design GDPR-compliant data models, including data identification, classification, and protection strategies. Compare and contrast enterprise data governance program approaches.
  • Large Data Volume (LDV) Considerations (20%): Design data models optimized for large data volumes and performance. Develop data archiving and purging plans. Understand when and how to utilize virtualized data.
  • Data Migration (15%): Recommend techniques for ensuring high data quality during data loading. Compare and contrast methods for improving performance when migrating large datasets. Understand data export options from Salesforce.

Exam Details

  • Format: 60 multiple-choice/multiple-select questions (+5 unscored)
  • Duration: 105 minutes
  • Passing Score: 58%
  • Exam Version: Spring ’23 release
  • Registration Fee: $400 USD (+ taxes, if applicable)
  • Retake Fee: $200 USD (+ taxes, if applicable)
  • Delivery: Proctored exam (onsite or online)
  • Prerequisite: None

Prepare for Success

This certification is a valuable asset for data architects aiming to build and maintain efficient and secure data solutions within the Salesforce ecosystem. Focus on understanding data modeling principles, MDM strategies, data governance best practices, and techniques for handling large data volumes.

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