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Data-Architect Exam Outline
Data modeling/Database Design: 25%
- 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).
- 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).
Master Data Management:
- 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 and use techniques for establishing a “golden record” or “system of truth” for the custom 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.
- Given a customer scenario, recommend appropriate approaches and techniques to capture and maintain customer references & metadata to preserve traceability and establish a common context for business rules
Salesforce Data Management:
- Given a customer scenario, recommend an appropriate combination of Salesforce license types to effectively leverage standard and custom objects to meet business needs.
- 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 a design to effectively consolidate and/or leverage data from multiple Salesforce instances.
- 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.
Large Data Volume considerations:
- Given a customer scenario, design a data model that scales considering large data volume and solution performance.
- Given a customer scenario, recommend a data archiving and purging plan that is optimal for the customer’s data storage management needs.
- Given a customer scenario, decide when to use virtualized data and describe virtualized data options.
- 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.
About the Data-Architect Exam:
- Questions: 60 multiple-choice/multiple-select questions
- Time allowed: 105 minutes
- Required Passing score: 58%