PDF Version DemoHow to study the Data-Architecture-And-Management-Designer Exam
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Who should take the Data-Architecture-And-Management-Designer exam
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.
Reference: https://trailhead.salesforce.com/en/credentials/dataarchitectureandmanagementdesigner#
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 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).
- 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 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%
- 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
- 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 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 a design to effectively consolidate and/or leverage data from multiple Salesforce instances.
- Given a customer scenario, recommend techniques to ensure data is persisted in a consistent manner.
- 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 appropriate combination of Salesforce license types to effectively leverage standard and custom objects to meet business needs.
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, design a data model that scales considering large data volume and solution performance.
- Given a customer scenario, decide when to use virtualised data and describe virtualised data options.
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.
Salesforce Data-Architecture-And-Management-Designer Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Data Integration and Migration | - Integration patterns and best practices - ETL and data loading tools (Data Loader, APIs) - Data migration planning and execution |
| Topic 2: Data Modeling and Management | - Data modeling strategies in Salesforce - Schema design and normalization concepts - Relationship modeling (lookup vs master-detail) |
| Topic 3: Large Data Volume Management | - Indexing and query optimization - Scalability design in Salesforce data architecture - Archiving and partitioning strategies |
| Topic 4: Master Data Management (MDM) | - Golden record strategy - Deduplication and data matching |
| Topic 5: Data Governance | - Data stewardship and lifecycle policies - Data quality management - Data security and compliance considerations |
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