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What is the duration of the Data-Architecture-And-Management-Designer Exam

• Number of Questions: 60
• Length of Examination: 105 minutes
• Format: Multiple choices, multiple answers
• 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.
• Passing Score: 58%

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

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

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Salesforce Data-Architecture-And-Management-Designer Exam

Salesforce Data-Architecture-And-Management-Designer Exam is related to Salesforce Certified Data Architecture and Management Designer (SU18) Certification. This exam validates the Candidate knowledge to assesses the architecture environment and requirements and designs sound, scalable, and performance solutions on the Lightning Platform. It also deals with the ability to meet the requirements of large-data-volume enterprises, as well as how they understand enterprise data management and stewardship concerns and considerations in relation to projects.

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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 customer scenario, recommend approaches and techniques to avoid data skew (record locking, sharing calculation issues, and excessive child to parent relationships).
• 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.
• 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 various techniques and considerations for designing a data model for the Customer 360 platform. (e.g. objects, fields & relationships, object features).

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 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.
• 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, 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%

• Given a customer scenario, recommend appropriate techniques and methods for ensuring high data quality at load time.
• Compare and contrast various techniques and considerations for exporting data from Salesforce.
• Compare and contrast various techniques for improving performance when migrating large data volumes into Salesforce.