Total 257 Questions
Last Updated On : 2-Jun-2025
Preparing with Data-Architect practice test is essential to ensure success on the exam. This Salesforce SP25 test allows you to familiarize yourself with the Data-Architect exam questions format and identify your strengths and weaknesses. By practicing thoroughly, you can maximize your chances of passing the Salesforce certification spring 2025 release exam on your first attempt. Surveys from different platforms and user-reported pass rates suggest Data-Architect practice exam users are ~30-40% more likely to pass.
An Architect needs to document the data architecture for a multi-system, enterprise Salesforce implementation. Which two key artifacts should the Architect use? (Choose two.)
A.
User stories
B.
Data model
C.
Integration specification
D.
Non-functional requirements
Data model
Integration specification
Explanation:
A Data Model defines the structure, relationships, and constraints of data entities, ensuring clarity in how data is stored and accessed. An Integration Specification outlines how data flows between systems, crucial for multi-system Salesforce implementations to avoid inconsistencies. User stories (A) focus on functionality, not architecture, while non-functional requirements (D) address performance, not data structure. Thus, B and C are essential for documenting data architecture, ensuring alignment across systems, scalability, and governance.
Get Cloudy Consulting uses an invoicing system that has specific requirements. One requirement is that attachments associated with the Invoice_c custom object be classified by Types (i.e., ""Purchase Order"", ""Receipt"", etc.) so that reporting can be performed on invoices showing the number of attachments grouped by Type. What should an Architect do to categorize the attachments to fulfill these requirements?
A.
Add additional options to the standard ContentType picklist field for the Attachment object.
B.
Add a ContentType picklist field to the Attachment layout and create additional picklist options.
C.
Create a custom picklist field for the Type on the standard Attachment object with the values.
D.
Create a custom object related to the Invoice object with a picklist field for the Type.
Create a custom object related to the Invoice object with a picklist field for the Type.
Explanation:
Standard Attachment or ContentDocument objects cannot be extended with custom picklists (A, B, C are invalid). A custom object linked to Invoice__c allows Type categorization via a picklist, enabling reporting. This solution adheres to Salesforce’s best practices for extensibility without modifying standard objects. It also future-proofs the solution for additional metadata needs.
Universal Containers (CU) is in the process of implementing an enterprise data warehouse (EDW). UC needs to extract 100 million records from Salesforce for migration to the EDW. What data extraction strategy should a data architect use for maximum performance?
A.
Install a third-party AppExchange tool.
B.
Call the REST API in successive queries.
C.
Utilize PK Chunking with the Bulk API.
D.
Use the Bulk API in parallel mode.
Utilize PK Chunking with the Bulk API.
Explanation:
PK Chunking splits large datasets into smaller chunks using primary keys, optimizing performance for massive data volumes. The Bulk API handles high-volume asynchronous jobs efficiently. REST API (B) has governor limits, and parallel mode (D) lacks chunking’s scalability. Third-party tools (A) add complexity. PK Chunking + Bulk API is Salesforce’s recommended approach for >1M records.
Northern Trail Outfitters (NTO) has a variety of customers that include householder, businesses, and individuals.
The following conditions exist within its system:
NTO has a total of five million customers.
Duplicate records exist, which is replicated across many systems, including Salesforce.
Given these conditions, there is a lack of consistent presentation and clear identification of a customer record. Which three option should a data architect perform to resolve the issues with the customer data?
A.
Create a unique global customer ID for each customer and store that in all system for referential identity.
B.
Use Salesforce CDC to sync customer data cross all systems to keep customer record in sync.
C.
Invest in data duplicate tool to de-dupe and merge duplicate records across all systems.
D.
Duplicate customer records across the system and provide a two-way sync of data between the systems.
E.
Create a customer master database external to Salesforce as a system of truth and sync the customer data with all systems.
Create a unique global customer ID for each customer and store that in all system for referential identity.
Invest in data duplicate tool to de-dupe and merge duplicate records across all systems.
Create a customer master database external to Salesforce as a system of truth and sync the customer data with all systems.
Explanation:
A global ID (A) ensures referential integrity across systems. A deduplication tool (C) merges duplicates systematically. A master database (E) centralizes truth, syncing downstream (CDC (B) syncs but doesn’t dedupe; D worsens duplicates). These steps standardize data, eliminate redundancy, and enforce consistency.
As part of addressing general data protection regulation (GDPR) requirements, UC plans to implement a data classification policy for all its internal systems that stores customer information including salesforce. What should a data architect recommend so that UC can easily classify consumer information maintained in salesforce under both standard and custom objects?
A.
Use App Exchange products to classify fields based on policy.
B.
Use data classification metadata fields available in field definition.
C.
Create a custom picklist field to capture classification of information on customer.
D.
Build reports for customer information and validate.
Use data classification metadata fields available in field definition.
Explanation:
Salesforce provides field-level metadata (e.g., ComplianceGroup) to classify sensitive data natively, aligning with GDPR. Custom picklists (C) or reports (D) are manual and error-prone. AppExchange tools (A) add overhead. Native metadata scales and integrates with Salesforce’s compliance features.
Cloud Kicks needs to purge detailed transactional records from Salesforce. The data should be aggregated at a summary level and available in Salesforce. What are two automated approaches to fulfill this goal? (Choose two.)
A.
Third-party Integration Tool (ETL)
B.
Schedulable Batch Apex
C.
Third-party Business Intelligence system
D.
Apex Triggers
Third-party Integration Tool (ETL)
Schedulable Batch Apex
Explanation:
Batch Apex automates large-scale data aggregation/deletion in Salesforce. ETL tools (e.g., MuleSoft) can extract, summarize, and archive data externally. Triggers (D) handle real-time ops, not batch purges. BI systems (C) analyze but don’t purge. A + B are scalable and automated.
Cloud Kicks has the following requirements:
- Data needs to be sent from Salesforce to an external system to generate invoices from their Order Management System (OMS).
- A Salesforce administrator must be able to customize which fields will be sent to the external system without changing code.
What are two approaches for fulfilling these requirements? (Choose two.)
A.
A set
B.
An Outbound Message to determine which fields to send to the OMS.
C.
A Field Set that determines which fields to send in an HTTP callout.
D.
Enable the field -level security permissions for the fields to send.
An Outbound Message to determine which fields to send to the OMS.
A Field Set that determines which fields to send in an HTTP callout.
Explanation:
Outbound Messages (B) allow admins to configure fields sent via workflow. Field Sets (C) let admins customize fields in HTTP callouts without code. FLS (D) controls access, not transmission. Set
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?
A.
Master-detail relationship filed on Account, related to Inventory_c
B.
Master-detail relationship filed on Inventory_c, related to Account
C.
Indirect lookup relationship field on Account, related to Inventory_c
D.
Lookup relationship fields on Inventory related to Account
Master-detail relationship filed on Inventory_c, related to Account
Explanation:
A master-detail on Inventory__c enforces parent Account’s sharing rules and cascade deletion (required per scenario). Lookup (D) lacks cascade delete. Indirect lookup (C) is for external objects. The child (Inventory) must reference the parent (Account).
Cloud Kicks is launching a Partner Community, which will allow users to register shipment requests that are then processed by Cloud Kicks employees. Shipment requests contain header information, and then a list of no more than 5 items being shipped.
First, Cloud Kicks will introduce its community to 6,000 customers in North America, and then to 24,000 customers worldwide within the next two years. Cloud Kicks expects 12 shipment requests per week per customer, on average, and wants customers to be able to view up to three years of shipment requests and use Salesforce reports. What is the recommended solution for the Cloud Kicks Data Architect to address the requirements?
A.
Create an external custom object to track shipment requests and a child external object to track shipment items. External objects are stored off-platform in Heroku’s Postgres database.
B.
Create an external custom object to track shipment requests with five lookup custom fields for each item being shipped. External objects are stored off-platform in Heroku’s Postgres database.
C.
Create a custom object to track shipment requests and a child custom object to track shipment items. Implement an archiving process that moves data off-platform after three years.
D.
Create a custom object to track shipment requests with five lookup custom fields for each item being shipped Implement an archiving process that moves data off-platform a three years.
Create a custom object to track shipment requests and a child custom object to track shipment items. Implement an archiving process that moves data off-platform after three years.
Explanation:
Storing in Salesforce (custom objects) meets reporting needs. A child object for items is scalable (vs. 5 lookups). Archiving off-platform after 3 years balances performance and compliance. External objects (A, B) lack reporting flexibility.
Cloud Kicks has the following requirements:
• Their Shipment custom object must always relate to a Product, a Sender, and a Receiver (all separate custom objects).
• If a Shipment is currently associated with a Product, Sender, or Receiver, deletion of those records should not be allowed.
• Each custom object must have separate sharing models.
What should an Architect do to fulfill these requirements?
A.
Associate the Shipment to each parent record by using a VLOOKUP formula field.
B.
Create a required Lookup relationship to each of the three parent records.
C.
Create a Master-Detail relationship to each of the three parent records.
D.
Create two Master-Detail and one Lookup relationship to the parent records.
Create a required Lookup relationship to each of the three parent records.
Explanation:
Required Lookups prevent deletion of referenced records (Product/Sender/Receiver) and allow separate sharing models (master-detail would inherit sharing, violating requirements). Formula fields (A) don’t enforce referential integrity.
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