What is the duration of the Data-Architecture-And-Management-Designer Exam
- Length of Examination: 105 minutes
- Number of Questions: 60
- Exam delivery options: Proctored exam delivered onsite at a testing center or in an online proctored environment. Click here for information on scheduling an exam.
- Format: Multiple choices, multiple answers
- Passing Score: 58%
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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%
- 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.
- 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 scenario, recommend approaches and techniques to design a scalable data model that obeys the current security and sharing model.
- 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).
- Given a customer scenario, recommend approaches and techniques to avoid data skew (record locking, sharing calculation issues, and excessive child to parent relationships).
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 approaches and techniques for consolidating data attributes from multiple sources. Discuss criteria and methodology for picking the winning attributes.
- 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 appropriate approaches and techniques to capture and maintain customer reference & metadata to preserve traceability and establish a common context for business rules
3. Salesforce Data Management: 25%
- 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.
- Given a customer scenario, recommend a design to effectively consolidate and/or leverage data from multiple Salesforce instances.
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%
- 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.
- Compare and contrast various techniques and considerations for exporting data from Salesforce.
Reference: https://trailhead.salesforce.com/en/credentials/dataarchitectureandmanagementdesigner#
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Salesforce Data-Architecture-And-Management-Designer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Governance | 10% | - Data classification and stewardship - Data governance framework - Compliance and data privacy (GDPR etc.) |
| Topic 2: Master Data Management | 5% | - Attribute consolidation and survivorship - Golden record and system of truth - Metadata and reference data management |
| Topic 3: Data Modeling and Database Design | 25% | - Standard, custom, and Big Objects - Data security and sharing model alignment - Data model design for Customer 360 - Relationships, lookup, master-detail |
| Topic 4: Data Migration | 15% | - Data quality and validation - Bulk load performance - Export and backup strategies - Migration tools and APIs |
| Topic 5: Salesforce Data Management | 25% | - License and object usage strategy - Virtual data and external objects - Multi-org data consolidation - Data persistence and consistency |
| Topic 6: Large Data Volume Considerations | 20% | - Archiving and data lifecycle management - Query optimization and SOQL best practices - Skinny tables and partitioning - Performance and indexing strategies |







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