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.Given a customer scenario, recommend appropriate techniques and methods for ensuring high data quality at load time.Given a customer scenario, decide when to use virtualised data and describe virtualised data options.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.Compare and contrast various approaches and considerations for designing and implementing an enterprise data governance program.Discuss the various options to identify, classify and protect personal and sensitive information. Given a customer scenario, recommend an approach for designing a GDPR compliant data model.Given a customer scenario, recommend a design to effectively consolidate and/or leverage data from multiple Salesforce instances.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 appropriate combination of Salesforce license types to effectively leverage standard and custom objects to meet business needs.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.Discuss criteria and methodology for picking the winning attributes. Given a customer scenario, recommend approaches and techniques for consolidating data attributes from multiple sources.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.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.) Compare and contrast the various techniques, approaches and considerations for implementing Master Data Management Solutions (e.g.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 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.business dictionary, data lineage, taxonomy, data classification). Compare and contrast various techniques, approaches and considerations for capturing and managing business and technical metadata (e.g.Given a scenario, recommend approaches and techniques to design a scalable data model that obeys the current security and sharing model.objects, fields & relationships, object features). Compare and contrast various techniques and considerations for designing a data model for the Customer 360 platform.Salesforce Certified Data Architect Exam Key Topics Data modeling/ Database Design: 25% Registration fee: USD 400, plus applicable taxes as required per local lawĪlways check Salesforce document for latest information.Time allotted to complete the exam: 105 minutes (time allows for unscored questions). Content: 60 multiple-choice/multiple-select questions.The Salesforce Certified Data Architecture and Management Designer exam has the following characteristics: Salesforce Certified Data Architect Exam Outline Five to eight years of experience supporting or implementing data-centric initiatives.
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