Free PDF Quiz 2026 Salesforce Plat-Arch-201: Useful Salesforce Certified Platform Data Architect Pass Guarantee

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Salesforce Plat-Arch-201 Exam Syllabus Topics:

SectionWeightObjectives
Data Modeling and Database Design25%- Metadata management
  • 1. Business dictionary, data lineage, taxonomy and classification
- Data skew prevention
  • 1. Avoid record locking, sharing issues and excessive parent-child relationships
- Data model design for Customer 360
  • 1. Scalable design aligned with security and sharing model
  • 2. Objects, fields, relationships and object features
- Object type selection
  • 1. Standard/custom objects vs Big Objects: use cases, pros and cons
Data Migration15%- Migration strategy and planning
  • 1. Assessment, mapping, validation and rollback planning
- Data quality and validation
  • 1. Cleaning, deduplication and post-migration verification
- Migration execution and tools
  • 1. Data loader, ETL tools and bulk API usage
Master Data Management5%- MDM implementation approaches
  • 1. Harmonization, consolidation, survivorship rules and thresholds
  • 2. Canonical modeling and hierarchy management
- Golden record and system of truth
  • 1. Establishing single source of truth in single org
Data Integration20%- Data synchronization and consistency
  • 1. Conflict resolution, data consistency and idempotency
- External data sources
  • 1. External Objects, OData and virtual data access
- Integration patterns and technologies
  • 1. Synchronous vs asynchronous, batch vs real-time
  • 2. APIs, middleware and external systems integration
Data Governance, Quality and Security15%- Data security and compliance
  • 1. Access control, encryption, compliance and audit
- Data governance framework
  • 1. Policies, standards, ownership and stewardship
- Data quality management
  • 1. Profiling, monitoring, cleansing and enrichment
Large Data Volumes and Performance20%- Storage and scalability planning
  • 1. Data volume growth planning and storage limits
- LDV architecture design
  • 1. Data distribution, archiving and partitioning strategies
- Query and performance optimization
  • 1. Indexing, selective queries and avoiding performance bottlenecks

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Salesforce Certified Platform Data Architect Sample Questions (Q171-Q176):

NEW QUESTION # 171
Which two best practices should be followed when using SOSL for searching?

Answer: B,D

Explanation:
The two best practices that should be followed when using SOSL for searching are: Keep searches specific and avoid wildcards where possible. Use Find in "ALL FIELDS" for faster searches. These best practices are helpful because they optimize the search performance and relevance. For example, keeping searches specific and avoiding wildcards where possible can reduce the number of results returned and improve the search accuracy. Using Find in "ALL FIELDS" for faster searches can leverage Salesforce's pre-defined indexes on common fields and return results more quickly than specifying individual fields.


NEW QUESTION # 172
Universal Containers wants to automatically archive all inactive Account data that is older than 3 years. The information does not need to remain accessible within the application. Which two methods should be recommended to meet this requirement? Choose 2 answer

Answer: A,D

Explanation:
Both C and D are valid methods to automatically archive and delete inactive Account data that is older than 3 years. You can use an ETL tool or the Data Loader to schedule jobs to export and delete data based on certain criteria.


NEW QUESTION # 173
North Trail Outfitters (NTO) operates a majority of its business from a central Salesforce org, NTO also owns several secondary orgs that the service, finance, and marketing teams work out of, At the moment, there is no integration between central and secondary orgs, leading to data- visibility issues.
Moving forward, NTO has identified that a hub-and-spoke model is the proper architect to manage its data, where the central org is the hub and the secondary orgs are the spokes.
Which tool should a data architect use to orchestrate data between the hub org and spoke orgs?

Answer: B

Explanation:
According to the Salesforce documentation, a hub-and-spoke model is an integration architecture pattern that allows connecting multiple Salesforce orgs using a central org (hub) and one or more secondary orgs (spokes). The hub org acts as the master data source and orchestrates the data flow between the spoke orgs. The spoke orgs act as the consumers or producers of the data and communicate with the hub org.
To orchestrate data between the hub org and spoke orgs, a data architect should use:
A middleware solution that extracts and distributes data across both the hub and spokes (option A). This means using an external service or tool that can connect to multiple Salesforce orgs using APIs or connectors, and perform data extraction, transformation, and distribution operations between the hub and spoke orgs. This can provide a scalable, flexible, and reliable way to orchestrate data across multiple orgs.


NEW QUESTION # 174
What ensures referential integrity?

Answer: A

Explanation:
Relationships ensure valid connections between records.


NEW QUESTION # 175
Universal Containers is planning out their archiving and purging plans going forward for their custom objects Topic__c and Comment__c. Several options are being considered, including analytics snapshots, offsite storage, scheduled purges, etc. Which three questions should be considered when designing an appropriate archiving strategy?

Answer: B,D,E

Explanation:
The three questions that should be considered when designing an appropriate archiving strategy are: If reporting is necessary, can the information be aggregated into fewer, summary records?
Will the data being archived need to be reported on or accessed in any way in the future? Are there any regulatory restrictions that will influence the archiving and purging plans? These questions are important because they help determine the scope, frequency, and method of archiving and purging data from Salesforce. For example, if reporting is necessary, then summary records or analytics snapshots can be used to store aggregated data and reduce the number of records that need to be archived. If the data being archived needs to be accessed in the future, then offsite storage or external objects can be used to retain the data and make it available on demand. If there are any regulatory restrictions, such as GDPR or HIPAA, then the archiving and purging plans need to comply with them and ensure data security and privacy


NEW QUESTION # 176
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