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Salesforce Data-Architect Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Governance and Compliance20%- Data lifecycle management
  • 1. Data retention and archiving policies
  • 2. Data privacy and security
  • 3. Data classification and handling
- Data governance framework
  • 1. Data stewardship and ownership
  • 2. Data quality standards
  • 3. Compliance and regulatory requirements
Topic 2: Large Data Volume Considerations20%- Performance and scalability
  • 1. Avoiding and resolving data skew
  • 2. Governor limits and bulk processing
  • 3. Handling millions of records
- Storage and optimization
  • 1. Storage limits and management
  • 2. Archiving and off-platform storage
  • 3. Performance tuning techniques
Topic 3: Data Integration and Master Data Management10%- Master data management
  • 1. MDM strategy and implementation
  • 2. Data synchronization and consistency
  • 3. Single source of truth design
- Integration patterns and tools
  • 1. External data sources and objects
  • 2. Real-time vs batch integration
  • 3. REST, SOAP, and Bulk API usage
Topic 4: Salesforce Data Management25%- Data import and export strategies
  • 1. Tools: Data Loader, Import Wizard, Bulk API
  • 2. Data validation and cleansing
  • 3. Migration planning and execution
- Sharing and visibility design
  • 1. Sharing rules, manual sharing, Apex sharing
  • 2. Data access and security model
  • 3. Organization-wide defaults, role hierarchy
Topic 5: Data Modeling and Database Design25%- Indexing and data structure
  • 1. Query optimization strategies
  • 2. Standard and custom indexes
  • 3. Skinny tables and big objects
- Design scalable data models
  • 1. Object relationships and cardinality
  • 2. Custom and standard object design
  • 3. Data model optimization for performance

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Salesforce Certified Data Architect Sample Questions (Q38-Q43):

NEW QUESTION # 38
Universal Containers (UC) is implementing a formal, cross -business -unit data governance program As part of the program, UC will implement a team to make decisions on enterprise -wide data governance. Which two roles are appropriate as members of this team? Choose 2 answers

Answer: A,C

Explanation:
Analytics/BI Owners and Data Domain Stewards are appropriate roles as members of a team that makes decisions on enterprise-wide data governance. Analytics/BI Owners are responsible for defining the business requirements and metrics for data analysis and reporting, and Data Domain Stewards are responsible for defining and enforcing the data quality standards and rules for specific data domains. Salesforce Administrators and Operational Data Users are not suitable roles for this team, as they are more focused on the operational aspects of data management, such as configuration, maintenance, and usage.


NEW QUESTION # 39
NTO processes orders from its website via an order management system (OMS). The OMS stores over 2 million historical records and is currently not integrated with SF. The Sales team at NTO using Sales cloud and would like visibility into related customer orders yet they do not want to persist millions of records directly in Salesforce. NTO has asked the data architect to evaluate SF connect and the concept of data verification. Which 3 considerations are needed prior to a SF Connect implementation?
Choose 3 answers:

Answer: B,D,E

Explanation:
The three considerations needed prior to a SF Connect implementation are to develop an object relationship strategy, identify the external tables to sync into external objects, and assess whether the external data source is reachable via an ODATA endpoint. SF Connect is a feature that allows integrating external data sources with Salesforce using external objects. External objects are similar to custom objects, but they store metadata only and not data. They enable on-demand access to external data via standard Salesforce APIs and user interfaces. To implement SF Connect, a data architect needs to consider how the external objects will relate to other objects in Salesforce, which external tables will be exposed as external objects, and whether the external data source supports ODATA protocol for data access.


NEW QUESTION # 40
Universal Containers has a large number of Opportunity fields (100) that they want to track field history on. Which two actions should an architect perform in order to meet this requirement? Choose 2 answers

Answer: B,C

Explanation:
Creating a custom object to store a copy of the record when changed and creating a custom object to store the previous and new field values are two possible actions that an architect can perform to meet the requirement of tracking field history on 100 Opportunity fields. A custom object can store more fields and records than the standard field history tracking feature, which has a limit of 20 fields per object and 18 or 24 months of data retention. A custom object can also be used for reporting and analysis of field history data. The other options are not feasible or effective for meeting the requirement


NEW QUESTION # 41
Universal Containers (UC) has multi -level account hierarchies that represent departments within their major Accounts. Users are creating duplicate Contacts across multiple departments. UC wants to clean the data so as to have a single Contact across departments. What two solutions should UC implement to cleanse their data?
Choose 2 answers

Answer: C,D

Explanation:
Making use of a third-party tool to help merge duplicate Contacts across Accounts and using Data.com to standardize Contact address information to help identify duplicates are two solutions that UC should implement to cleanse their data and have a single Contact across departments. A third-party tool, such as an app from the AppExchange, can provide advanced features and capabilities for finding and merging duplicate Contacts across different Accounts, based on various criteria and rules. Data.com can provide address verification and standardization services that can enhance the quality and consistency of Contact address information and make it easier to identify duplicates. The other options are not feasible or effective for cleansing the data, as they would either not work across different Accounts, not address the root cause of duplication, or not provide sufficient functionality for merging duplicates


NEW QUESTION # 42
Universal Containers (UC) is in the process of migrating lagacy inventory data from an enterprise resources planning (ERP) system into Sales Cloud with the following requirements:
Legacy inventory data will be stored in a custom child objects called Inventory_c.
Inventory data should be related to the standard Account object.
The Inventory_c object should Inhent the same sharing rules as the Account object.
Anytime an Account record is deleted in Salesforce, the related Inventory_c record(s) should be deleted as well.
What type of relationship field should a data architect recommend in this scenario?

Answer: A


NEW QUESTION # 43
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