Free PDF Pass-Sure Salesforce - Plat-Arch-201 - Salesforce Certified Platform Data Architect Test Lab Questions

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Salesforce Plat-Arch-201 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Integration20%- External data sources
  • 1. External Objects, OData and virtual data access
- Data synchronization and consistency
  • 1. Conflict resolution, data consistency and idempotency
- Integration patterns and technologies
  • 1. APIs, middleware and external systems integration
  • 2. Synchronous vs asynchronous, batch vs real-time
Topic 2: 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
Topic 3: Data Migration15%- Data quality and validation
  • 1. Cleaning, deduplication and post-migration verification
- Migration strategy and planning
  • 1. Assessment, mapping, validation and rollback planning
- Migration execution and tools
  • 1. Data loader, ETL tools and bulk API usage
Topic 4: Master Data Management5%- Golden record and system of truth
  • 1. Establishing single source of truth in single org
- MDM implementation approaches
  • 1. Canonical modeling and hierarchy management
  • 2. Harmonization, consolidation, survivorship rules and thresholds
Topic 5: Data Modeling and Database Design25%- Data model design for Customer 360
  • 1. Scalable design aligned with security and sharing model
  • 2. Objects, fields, relationships and object features
- Data skew prevention
  • 1. Avoid record locking, sharing issues and excessive parent-child relationships
- Object type selection
  • 1. Standard/custom objects vs Big Objects: use cases, pros and cons
- Metadata management
  • 1. Business dictionary, data lineage, taxonomy and classification
Topic 6: 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 (Q51-Q56):

NEW QUESTION # 51
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: A

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 # 52
Universal Containers (UC) has 1,000 accounts and 50,000 opportunities. UC has an enterprise security requirement to export all sales data outside of Salesforce on a weekly basis. The security requirement also calls for exporting key operational data that includes events such as file downloads, logins, logouts, etc. Which two recommended approaches would address the above requirement?

Answer: B,C

Explanation:
Using Weekly Export to extract transactional data to on-premise systems and using Event Monitoring to extract event data to on-premise systems are two recommended approaches that would address the security requirement of UC. Weekly Export is a built-in feature that allows UC to download a zip file of their Salesforce data on a weekly basis. Event Monitoring is a tool that allows UC to access detailed information about various events that occur in their Salesforce org, such as logins, logouts, file downloads, etc.


NEW QUESTION # 53
UC has to built a B2C ecommerce site on Heroku that shares customer and order data with a Heroku Postgres database. UC is currently utilizing Postgres as the single source of truth for both customers and orders. UC has asked a data architect to replicate the data into salesforce so that salesforce can now act as the system of record. What are the 3 considerations that data architect should weigh before implementing this requirement? Choose 3 answer

Answer: D,E,F

Explanation:
Before replicating the data from Heroku Postgres to Salesforce, the data architect should consider the following factors:
Whether the data is a driver of key processes implemented within Salesforce. For example, if the data is used for workflows, triggers, or validation rules, it should be replicated to Salesforce.
Whether there is a tight relationship between order data and an enterprise resource planning (ERP) application. For example, if the order data needs to be synchronized with the ERP system, it should be replicated to Salesforce.
The selection of the tool required to replicate the data. For example, Heroku Connect can be used to bi-directionally sync data between Heroku Postgres and Salesforce


NEW QUESTION # 54
A national nonprofit organization is using Salesforce to recruit members. The recruitment process requires a member to be matched with a volunteer opportunity. Given the following:
1. A record is created in Project__ c and used to track the project through completion.
2. The member may then start volunteering and is required to track their volunteer hours, which is stored in VTOTime_c object related to the project.
3. Ability to view or edit the VTOTime__c object needs to be the same as the Project__ c record.
4. Managers must see total hours volunteered while viewing the Project__ c record.
Which data relationship should the data architect use to support this requirement when creating the custom VTOTime__c object?

Answer: B

Explanation:
A master-detail field on VTOTime__c to Project__c is the data relationship that the data architect should use to support the requirement when creating the custom VTOTime__c object. A master- detail relationship creates a parent-child relationship between two objects, where the master record controls certain behaviors of the detail record, such as security, ownership, deletion, and roll-up summary fields. By using a master-detail field on VTOTime__c to Project__c, you can ensure that the ability to view or edit the VTOTime__c object is the same as the Project__c record, and that managers can see the total hours volunteered while viewing the Project__c record using a roll-up summary field.


NEW QUESTION # 55
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 answer

Answer: A,B

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 # 56
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