Salesforce Data Architect practice exam

*** EXPLANATION TO EACH QUESTION INCLUDED ***

NO DUPLICATED QUESTIONS.

BEST QUESTIONS TO PREPARE FOR YOUR SALESFORCE DATA ARCHITECT EXAM.

UP TO DATE WITH CURRENT SALESFORCE RELEASE.

Are you preparing for the Salesforce Data Architect certification exam and looking for a comprehensive and reliable practice test set to help you ace the test? Look no further! Our practice exam set is designed to simulate the real exam experience and cover all the topics you need to know to pass the exam on your first try.

Prepare for your Salesforce Data Architect examination: pre-defined set of questions, with verified answers, to cover all certifications areas will improve your overall score and allow you to pass the real Salesforce certification easily.

All examination sections are covered in this course.

Practice test will help you to evaluate your certification readiness.

You will get your result just after you finish your exam and you can focus on improving from certification specific areas. These exam questions are well selected and verified and are similar to actual exam questions, which will help you get familiar with all Salesforce Data Architect exam topics.

For each question you will find explanation about the context, best answer and possible Salesforce solutions.

With detailed explanations and references to the Salesforce documentation, you'll gain a deep understanding of the concepts and best practices needed to succeed in your Salesforce Data Architect examination.

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Salesforce Data Architect exam sections

Below are all the sections, which will be tested during the exam.

A candidate should have a hands-on experience and deep understanding of the following areas.

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: 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 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.

• 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.

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 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.

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.

Large Data Volume considerations: 20%

• 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 customer's data storage management needs.

• Given a customer scenario, decide when to use virtualized data and describe virtualized data options.

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 for improving performance when migrating large data volumes into Salesforce.

• Compare and contrast various techniques and considerations for exporting data from Salesforce.