Data-Architect Practice Exam Questions Spring 2025 Page 4

Universals Containers’ system administrators have been complaining that they are not able to make changes to its users’ record, including moving them to new territories without getting “unable to lock row” errors. This is causing the system admins to spend hours updating user records every day. What should the data architect do to prevent the error?

A.

Reduce number of users updated concurrently.

B.

Enable granular locking.

C.

Analyze Splunk query to spot offending records.

D.

Increase CPU for the Salesforce org.

B.

Enable granular locking.

Explanation:

Correct Answer (B): Enable granular locking to prevent "unable to lock row" errors by allowing smaller, concurrent updates to user records, reducing contention and improving admin efficiency without batch restrictions.

Why Others Fail:

A: Reducing concurrent updates delays processes but doesn’t resolve the root locking issue.
C: Splunk identifies errors but doesn’t prevent them during record updates.
D: CPU boosts don’t address row-locking conflicts in Salesforce transactions.

Northern Trail Outfitters (NTO) wants to implement backup and restore for Salesforce data, Currently, it has data backup processes that runs weekly, which back up all Salesforce data to an enterprise data warehouse (EDW). NTO wants to move to daily backups and provide restore capability to avoid any data loss in case of outage. What should a data architect recommend for a daily backup and restore solution?

A.

Use AppExchange package for backup and restore.

B.

Use ETL for backup and restore from EDW.

C.

Use Bulk API to extract data on daily basis to EDW and REST API for restore.

D.

Change weekly backup process to daily backup, and implement a custom restore solution.

A.

Use AppExchange package for backup and restore.

Explanation:

Use an AppExchange package like OwnBackup or Gearset for automated daily backups and restore capabilities, ensuring compliance, minimal manual effort, and point-in-time recovery directly within Salesforce.

Why Others Fail:

B: ETL backups lack native restore features and require complex manual processes for recovery.
C: Bulk API extracts data but doesn’t provide streamlined, user-friendly restore functionality.
D: Custom solutions are costly, time-consuming, and prone to errors compared to pre-built tools.

How can an architect find information about who is creating, changing, or deleting certain fields within the past two months?

A. Remove "customize application" permissions from everyone else.

B. Export the metadata and search it for the fields in question.

C. Create a field history report for the fields in question.

D. Export the setup audit trail and find the fields in question.

Explanation:

Export the Setup Audit Trail to track all metadata changes (create/edit/delete) by user and timestamp, filtering for specific fields over the past two months.

Why Others Fail:

❌ A: Removing permissions disrupts workflows but doesn’t provide historical change data.
❌ B: Metadata exports show current state, not who made changes or when.
❌ C: Field History tracks record data, not schema changes

Every year, Ursa Major Solar has more than 1 million orders. Each order contains an average of 10 line items. The Chief Executive Officer (CEO) needs the Sales Reps to see how much money each customer generates year-over-year. However, data storage is running low in Salesforce. Which approach for data archiving is appropriate for this scenario?

A. 1. Annually export and delete order line items.
2. Store them in a zip file in case the data is needed later.

B. 1. Annually aggregate order amount data to store in a custom object.
2. Delete those orders and order line items.

C. 1. Annually export and delete orders and order line items.
2. Store them in a zip file in case the data is needed later.

D. 1. Annually delete orders and order line items.
2. Ensure the customer has order information in another system.

B. 1. Annually aggregate order amount data to store in a custom object.
2. Delete those orders and order line items.

Explanation:

To manage storage and still meet the CEO’s reporting needs, aggregate order revenue per customer annually into a custom object. This retains key business insights like year-over-year revenue without storing every detailed order or line item. Then, safely delete the detailed records to free up storage in Salesforce.

Universal Containers (UC) is launching an RFP to acquire a new accounting product available on AppExchange. UC is expecting to issue 5 million invoices per year, with each invoice containing an average of 10 line items. What should UC's Data Architect recommend to ensure scalability?

A.

Ensure invoice line items simply reference existing Opportunity line items.

B.

Ensure the account product vendor includes Wave Analytics in their offering.

C.

Ensure the account product vendor provides a sound data archiving strategy.

D.

Ensure the accounting product runs 100% natively on the Salesforce platform.

C.

Ensure the account product vendor provides a sound data archiving strategy.

Explanation:

The Data Architect should prioritize scalability and data volume management by recommending that the accounting product vendor provides a sound data archiving strategy (Option C). With 5 million invoices annually (50 million line items), UC risks hitting Salesforce storage limits and performance degradation without a plan to archive or offload historical data. A robust archiving strategy—such as automated purges, Big Objects, or external storage integration—ensures the system remains responsive while retaining compliance access to older records. This approach addresses the core challenge of volume without compromising functionality.

Why Others Fail:

Referencing Opportunity Line Items (Option A):
While this reduces redundancy, it doesn’t solve the sheer volume of invoice line items. Performance would still suffer as the database grows exponentially.

Wave Analytics (Option B):
Analytics tools are useful for reporting but irrelevant to transactional scalability. They don’t mitigate storage or processing loads from millions of records.

100% Native Platform (Option D):
Native tools simplify integration but lack built-in solutions for massive data volumes. Archiving is still necessary to avoid platform limits.Revoking "Customize Application" permissions (Option A) prevents future changes but provides no historical data, leaving past modifications untraceable.

Universal Containers (UC) is building a Service Cloud call center application and has a multi-system support solution. UC would like or ensure that all systems have access to the same customer information. What solution should a data architect recommend?

A.

Make Salesforce the system of record for all data.

B.

Implement a master data management (MDM) strategy for customer data.

C.

Load customer data in all systems.

D.

Let each system be an owner of data it generates.

B.

Implement a master data management (MDM) strategy for customer data.

Explanation:

B. Implement a master data management (MDM) strategy for customer data.
Why? MDM creates a single, trusted source of customer data shared across all systems, eliminating duplicates and inconsistencies.
Best for: Multi-system environments where data must stay synchronized (like UC’s call center).

Why Others Fail:

A. Make Salesforce the system of record
Forces all systems to depend on Salesforce, which may not suit systems needing autonomy (e.g., legacy tools).

C. Load customer data in all systems
Causes data redundancy, sync delays, and inconsistencies (e.g., updates in one system won’t reflect elsewhere).

D. Let each system own its data
Leads to fragmented, conflicting data (e.g., different contact info in different systems).

A company wants to document the data architecture of a Salesforce organization. What are two valid metadata types that should be included? (Choose two.)

A.

RecordType

B.

Document

C.

CustomField

D.

SecuritySettings

A.

RecordType

C.

CustomField

Explanation:

✅ A. RecordType – Defines different business processes, picklist values, and page layouts for the same object, making it crucial for understanding data structure and behavior.
✅ C. CustomField – Represents custom data fields created in Salesforce, which are fundamental to documenting the organization's unique data model.

Why Others Fail:

❌ B. Document: While documents can store information, they are not metadata types that define Salesforce's data architecture.
❌ D. SecuritySettings: Though important for access control, security settings are more about permissions than data structure.

Due to security requirements, Universal Containers needs to capture specific user actions, such as login, logout, file attachment download, package install, etc. What is the recommended approach for defining a solution for this requirement?

A.

Use a field audit trail to capture field changes.

B.

Use a custom object and trigger to capture changes.

C.

Use Event Monitoring to capture these changes.

D.

Use a third-party AppExchange app to capture changes.

C.

Use Event Monitoring to capture these changes.

Explanation:

Event Monitoring is Salesforce's native solution for tracking user activity logs, including logins, logouts, file downloads, package installs, and other security-related events. It provides detailed API-based analytics without requiring custom code or third-party tools.

Why Others Fail:

A. Field Audit Trail → Only tracks field-level changes, not user actions like logins or file downloads.
B. Custom Object & Trigger → Requires manual development, may miss critical system events, and is harder to maintain.
D. Third-Party AppExchange App → Adds unnecessary cost & complexity when Salesforce already offers Event Monitoring.

DreamHouse Realty has a Salesforce deployment that manages Sales, Support, and Marketing efforts in a multi-system ERP environment. The company recently reached the limits of native reports and dashboards and needs options for providing more analytical insights. What are two approaches an Architect should recommend? (Choose two.)

A.

Weekly Snapshots

B.

Einstein Analytics

C.

Setup Audit Trails

D.

AppExchange Apps

B.

Einstein Analytics

D.

AppExchange Apps

Explanation:

B. Einstein Analytics (now Tableau CRM)
Advanced Analytics: Provides AI-powered dashboards, predictive insights, and interactive data exploration beyond standard reports.
Multi-System Integration: Pulls data from Salesforce and external ERP systems into a unified analytics platform.

D. AppExchange Apps
Pre-Built Solutions: Apps like Tableau, Power BI, or Domo offer specialized reporting/analytics without custom development.
ERP Integration: Many apps connect natively to multi-system environments (e.g., SAP, Oracle).

Why Others Fail:

A. Weekly Snapshots: Only captures historical data at fixed intervals—no real-time insights or advanced analytics.
C. Setup Audit Trails: Tracks admin changes, not business data for analytical use.

A Salesforce customer has plenty of data storage. Sales Reps are complaining that searches are bringing back old records that aren't relevant any longer. Sales Managers need the data for their historical reporting. What strategy should a data architect use to ensure a better user experience for the Sales Reps?

A.

Create a Permission Set to hide old data from Sales Reps.

B.

Use Batch Apex to archive old data on a rolling nightly basis.

C.

Archive and purge old data from Salesforce on a monthly basis.

D.

Set data access to Private to hide old data from Sales Reps.

B.

Use Batch Apex to archive old data on a rolling nightly basis.

Explanation:

✅ B. Use Batch Apex to archive old data
This approach helps maintain historical data needed by Sales Managers while reducing clutter for Sales Reps.
Archiving involves moving older, less relevant records to:
1. A custom object
2. A different storage layer (e.g., Big Objects or external system)
Batch Apex is ideal for processing large volumes of data in the background, and running it nightly ensures data is continuously maintained.

Why Others Fail:

A. Permission Sets / D. Private Data Access: Hiding data doesn’t remove it from search indexes, so irrelevant records still appear.
C. Monthly Purges: Deleting data risks losing historical insights Sales Managers need.

Data-Architect Practice Test Questions