Salesforce Certified Data Architecture and Management Designer (Data-Architecture-And-Management-Designer日本語版) - testinsides Data-Architecture-And-Management-Designer日本語 dumps

Data-Architecture-And-Management-Designer日本語 real exams

Exam Code: Data-Architecture-And-Management-Designer-JPN

Exam Name: Salesforce Certified Data Architecture and Management Designer (Data-Architecture-And-Management-Designer日本語版)

Updated: Aug 16, 2026

Q & A: 224 Questions and Answers

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Data-Architecture-And-Management-Designer Exam topics

Candidates must know the exam topics before they start of preparation. Because it will really help them in hitting the core. Our Salesforce Data-Architecture-And-Management-Designer exam dumps will include the following topics:

1. Data Modeling/ Database Design 20%

  • 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 and considerations for designing a data model for the Customer 360 platform. (e.g. objects, fields & relationships, object features).
  • Given a customer scenario, recommend approaches and techniques to avoid data skew (record locking, sharing calculation issues, and excessive child to parent relationships).
  • Compare and contrast various techniques, approaches and considerations for capturing and managing business and technical metadata (e.g. business dictionary, data lineage, taxonomy, data classification).
  • Compare and contrast the different reasons for implementing Big Objects vs Standard/Custom objects within a production instance, alongside the unique pros and cons of utilizing Big Objects in a Salesforce data model.

2. Master Data Management: 5%

  • Compare and contrast the various techniques, approaches and considerations for implementing Master Data Management Solutions (e.g. MDM implementation styles, harmonizing & consolidating data from multiple sources, establishing data survivorship rules, thresholds & weights, leveraging external reference data for enrichment, Canonical modeling techniques, hierarchy management.)
  • Given a customer scenario, recommend appropriate approaches and techniques to capture and maintain customer reference & metadata to preserve traceability and establish a common context for business rules
  • 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.

3. Salesforce Data Management: 25%

  • Given a customer scenario, recommend a design to effectively consolidate and/or leverage data from multiple Salesforce instances.
  • Given a customer scenario, recommend appropriate combination of Salesforce license types to effectively leverage standard and custom objects to meet business needs.
  • 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 techniques to ensure data is persisted in a consistent manner.

4. Data Governance: 10%

  • Compare and contrast various approaches and considerations for designing and implementing an enterprise data governance program.
  • Given a customer scenario, recommend an approach for designing a GDPR compliant data model. Discuss the various options to identify, classify and protect personal and sensitive information.

5. Large Data Volume considerations: 20%

  • Given a customer scenario, recommend a data archiving and purging plan that is optimal for customer's data storage management needs.
  • Given a customer scenario, decide when to use virtualised data and describe virtualised data options.
  • Given a customer scenario, design a data model that scales considering large data volume and solution performance.

6. Data Migration: 15%

  • Compare and contrast various techniques and considerations for exporting data from Salesforce.
  • 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 large data volumes into Salesforce.

Certification Path

Salesforce Administrator Certification is a prerequisite for this exam.

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Reference: https://trailhead.salesforce.com/en/credentials/dataarchitectureandmanagementdesigner#

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Salesforce Certified Data Architecture and Management Designer certification is an internationally-recognized validation that identifies persons who earn it as possessing skilled as a Salesforce Certified Data Architecture and Management Designer. If a candidate wants significant improvement in career growth needs enhanced knowledge, skills, and talents. The Salesforce Data-Architecture-And-Management-Designer Exam provides proof of this advanced knowledge and skill. If a candidate has knowledge of associated technologies and skills that are required to pass the Salesforce Data-Architecture-And-Management-Designer Exam then he should take this exam.

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Salesforce Data-Architecture-And-Management-Designer日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Master Data Management5%- Attribute consolidation and survivorship
- Metadata and reference data management
- Golden record and system of truth
Topic 2: Data Migration15%- Bulk load performance
- Migration tools and APIs
- Export and backup strategies
- Data quality and validation
Topic 3: Data Modeling and Database Design25%- Relationships, lookup, master-detail
- Data model design for Customer 360
- Standard, custom, and Big Objects
- Data security and sharing model alignment
Topic 4: Data Governance10%- Data governance framework
- Compliance and data privacy (GDPR etc.)
- Data classification and stewardship
Topic 5: Salesforce Data Management25%- License and object usage strategy
- Multi-org data consolidation
- Data persistence and consistency
- Virtual data and external objects
Topic 6: Large Data Volume Considerations20%- Query optimization and SOQL best practices
- Skinny tables and partitioning
- Performance and indexing strategies
- Archiving and data lifecycle management

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