The benefit in Obtaining the Data-Architecture-And-Management-Designer Exam Certification

• When an organization hiring or promotion an employee, then the decision is made by human resources. Now while Candidate may have an IT background, they do their decisions in a way that takes into record many different factors. One thing is candidates have formal credentials, such as the Salesforce Certified Data Architecture and Management Designer.
• A candidate might have incredible IT skills. Employers that do the hiring need to make decisions based on limited information and as it always. When they view the official Salesforce Certified Data Architecture and Management Designer certification, they can be guaranteed that a candidate has achieved a certain level of competence.
• After completing the Salesforce Certified Data Architecture and Management Designer certification Candidate becomes a solid, well-rounded Salesforce Certified Data Architecture and Management Designer.
• If the Candidate has the desire to move up to a higher-paying position in an organization. This certification will help as always.

How much Data-Architecture-And-Management-Designer Exam Cost

The price of the Salesforce Data-Architecture-And-Management-Designer exam is $400 USD and exam retake fee is $200 USD.

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Data-Architecture-And-Management-Designer Exam Reference

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%

• 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).
• Compare and contrast various techniques and considerations for designing a data model for the Customer 360 platform. (e.g. objects, fields & relationships, object features).
• 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.
• 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%

• Given a customer scenario, recommend approaches and techniques for consolidating data attributes from multiple sources. Discuss criteria and methodology for picking the winning attributes.
• 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

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%

• 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.
• Compare and contrast various approaches and considerations for designing and implementing an enterprise data governance program.

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.

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