Salesforce Data Architect Credential
The Salesforce Certified Data Architect credential is intended for the architect who assesses the architecture environment and requirements; and designs sound, scalable, and performant solutions on the Customer 360 platform. The Architect will also have experience working with the following:
◉ Data Modeling & Database Design
◉ Master Data Management
◉ Salesforce Data Management
◉ Data Governance
◉ Large Data Volume Considerations
◉ Data Migration
The architect has experience communicating solutions and design trade-offs to business and IT stakeholders.
Purpose of this Exam Guide
This exam guide is designed to help you evaluate your readiness to successfully complete the Salesforce Certified Data Architect certification exam. This guide provides information about the target audience for the certification exam, recommended training and documentation, and a complete list of exam objectives—all with the intent of helping you achieve a passing score. Salesforce highly recommends a combination of on-the-job experience and self-study to maximize your chances of passing the exam.
Audience Description
A Salesforce Certified Data Architect assesses the architecture environment and requirements and designs sound, scalable, and performant solutions on the Customer 360 Platform as it pertains to enterprise data management. The candidate is knowledgeable about information architecture frameworks covering major building blocks, such as data sourcing, integration/movement, persistence, master data management, metadata management and semantic reconciliation, data governance, security, and delivery.
The candidate also has experience assessing customers' requirements in regards to data quality needs and creating solutions to ensure high quality data (e.g. no duplicates, correct data) and can also recommend organizational changes to ensure proper data stewardship. The candidate has experience communicating solutions and design trade-offs to business stakeholders.
The Salesforce Certified Data Architect has the following background:
◉ 2 to 3 years of Salesforce experience
◉ 5+ years of experience supporting or implementing data-centric solutions
Typical job roles may include:
◉ Advanced Administrator
◉ Data Architect
◉ Technical/Solution Architect
◉ Advanced Platform Developer
The Salesforce Certified Data Architect candidate has the experience, skills, and knowledge of the following:
◉ Data modeling/Database Design
◉ Custom fields, master detail, lookup relationships
◉ Client requirements and mapping to database requirements
◉ Standard object structure for sales and service cloud
◉ Making best use of Salesforce standard and big objects
◉ Association between standard objects and Salesforce license types
◉ Large Data Volume considerations
◉ Indexing, LDV migrations, performance
◉ Salesforce Platform declarative and programming concepts
◉ Scripting using those tools (Data loader, ETL platforms)
◉ Data Stewardship
◉ Data Quality Skills (concerned with clean data)
A candidate for this exam is not expected to know the following:
◉ Non-Salesforce Technology/Database Concepts
◉ Configuration of Integration tools
◉ Experience with MDM Tools (Master Data Management)
◉ Lightning Development Experience/Expertise
◉ Programming Language(s)
Recommended but not required - Salesforce Certified Platform App Builder, Platform Developer I, and Platform Developer II.
Salesforce Data Architect Exam Summary:
| Exam Name | Salesforce Certified Data Architect |
| Exam Code | Data Architect |
| Exam Price | Registration fee: $400 USD Retake fee: $200 USD |
| Duration | 105 minutes |
| Number of Questions | 60 |
| Passing Score | 58% |
| Recommended Training / Books | Architect Journey: Data Architect |
| Sample Questions | Salesforce Data Architect Sample Questions |
| Recommended Practice | Salesforce Certified Data Architect Practice Test |
Salesforce Data Architect Syllabus:
| Section | Objectives | Weights |
| Data modeling/Database Design | - 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). |
25% |
| 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 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. |
5% |
| Salesforce Data Management | - 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. |
25% |
| Data Governance | - 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. |
10% |
| 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 customer's data storage management needs. - Given a customer scenario, decide when to use virtualised data and describe virtualised data options. |
20% |
| Data Migration | - 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. |
15% |
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