SF-Data-Arch Practice Test 11 — 15 Questions

Question 1

A Salesforce architect is migrating 2 million legacy Contact records into a new Salesforce org. The legacy system does not have email addresses for 40% of the contacts, but Salesforce's standard Email field is not required. During a test load of 10,000 records using the Bulk API in serial mode, the load succeeds but the architect notices that duplicate contacts are being created because the legacy system reused a 'legacy_id__c' external ID field for different contacts across regions. What should the architect do to prevent duplicate creation during the full migration?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Create a new unique external ID field by concatenating region and legacy_id, populate it in the source data, and use it as the external ID for upsert operations.. The duplicate creation is due to the external ID field not being unique across regions. The correct solution is to create a new composite external ID that combines region and legacy ID, ensuring uniqueness. This allows upsert operations to correctly identify records and prevent duplicates, while the original legacy ID can be retained for audit purposes.

Answer

Set the legacy_id__c field as unique in Salesforce and retry the load; Salesforce will automatically reject duplicate external IDs.

Answer

Enable the 'Prevent Duplicates' setting on the Contact object and use Data Loader's deduplication feature before loading.

Answer

Use the Bulk API in parallel mode with a batch size of 1 to ensure each record is processed individually and duplicates are avoided.

Question 2

A Salesforce org is implementing a data governance program to manage data quality for a large volume of customer records. The architect must recommend tools and features to monitor and improve data quality on an ongoing basis. Which two Salesforce features should be used to proactively identify and address data quality issues? (Choose two.)

Accepted Answer

Duplicate Management with Matching Rules and Duplicate Rules. Duplicate Management and Validation Rules are proactive features that identify and prevent data quality issues. Duplicate Management detects and manages duplicate records, while Validation Rules enforce data quality at entry by blocking invalid saves. Data Loader, Salesforce Optimizer, and Reports/Dashboards are not proactive data quality tools; they serve other purposes like data loading, org optimization, or monitoring.

Answer

Data Loader with batch size optimization

Answer

Salesforce Optimizer

Answer

Reports and Dashboards with custom report types

Question 3

A large university is modeling academic records in Salesforce. Each Course can be taught by multiple Instructors, and each Instructor can teach multiple Courses. The university must report on the aggregate number of Courses each Instructor is teaching per semester and enforce that an Instructor cannot be assigned to the same Course twice within the same semester. Which data modeling approach should the architect implement?

Accepted Answer

Create a junction object Course_Instructor__c with two Master-Detail relationships (to Course and Instructor) plus a semester field, and configure a unique composite key across Course, Instructor, and Semester.. A junction object with two Master-Detail relationships is the standard Salesforce pattern for many-to-many relationships, and it enables roll-up summary fields on both parents. Adding a semester field and a unique composite key satisfies the duplicate-prevention rule. Reciprocal lookups, asymmetric relationships, and multi-select picklists cannot simultaneously support per-assignment attributes, aggregate reporting, and uniqueness enforcement.

Answer

Store Instructor assignments as a multi-select picklist on the Course object and use a formula field to count selections.

Answer

Create a Lookup relationship from Course to Instructor and from Instructor to Course, then build a report to deduplicate overlapping assignments.

Answer

Create a single Course_Instructor__c object with a Master-Detail to Course and a Lookup to Instructor, then use a validation rule to count existing records.

Question 4

A data architect is designing a data retention policy for a custom object Event_Log__c that stores 20 million records per year. The business requires that records older than 2 years be archived but still accessible for occasional reporting. What is the most appropriate approach?

Accepted Answer

Use Salesforce Big Objects to store archived records and query them via Async SOQL.. For high-volume, low-access data that must be retained and occasionally queried, Big Objects with Async SOQL provide a scalable, cost-effective archival solution. They allow storage of billions of records without impacting standard object performance. Deletion or moving to another custom object does not address the scale and accessibility requirements. Field history tracking is not a full archival mechanism.

Answer

Enable field history tracking on all fields and rely on it for archival.

Answer

Move records to a custom object with a lookup to the original record and use standard reports.

Answer

Create a scheduled batch job that deletes records older than 2 years.

Question 5

A healthcare company is migrating 4 million Patient__c records from a legacy system into Salesforce. The legacy extract includes a field named 'last_modified' that is populated for 99.8% of records, but the remaining 0.2% have a null value. The target external ID field requires a unique, non-null value. What should the data architect do to ensure a successful migration?

Accepted Answer

Generate a synthetic unique value for the records with null last_modified by using the legacy primary key concatenated with a timestamp, and map that to the external ID field.. The external ID field must contain a unique, non-null value for every record to support upsert and maintain data integrity. Generating a synthetic value from the legacy primary key and a timestamp ensures uniqueness and populates the field for the 0.2% of records with missing last_modified. This avoids data loss and meets the field constraint without modifying the source system or relaxing the Salesforce field definition.

Answer

Set the external ID field to allow nulls in the field definition, then migrate the records with null values as-is.

Answer

Use the standard Salesforce Data Loader's 'Insert' operation instead of 'Upsert' to bypass the external ID requirement.

Answer

Exclude the 0.2% of records with null last_modified from the migration and document them as exceptions for manual entry later.

Question 6

A company maintains a custom object Asset__c with 5 million records. They need to archive records older than 7 years to a Big Object for compliance. After archiving, the records must be queryable via SOQL for audits, but not editable. Which approach should an architect recommend?

Accepted Answer

Create a Big Object with the same fields, use a batch Apex job to copy old records, and then delete them from Asset__c. Provide audit access via a Lightning component that uses Async SOQL to query the Big Object.. Big Objects are the Salesforce-native solution for archiving massive datasets. They support high-volume storage and are queried asynchronously using Async SOQL, which is suitable for audit scenarios where real-time access is not required. Copying old records to a Big Object and deleting them from the transactional object reduces the object's size, improving query and DML performance. A Lightning component can invoke Async SOQL to retrieve archived records for audits.

Answer

Create a Big Object with the same fields as Asset__c, use a batch Apex job to copy old records, and then delete them from Asset__c. Provide audit access via a Visualforce page that queries the Big Object using SOQL.

Answer

Create a custom object Asset_Archive__c to store old records, and use a batch Apex job to move them. Provide audit access via standard reports and list views.

Answer

Use Salesforce Connect to create an external object that points to an external database containing the archived records, and provide audit access via external object list views.

Question 7

A data architect at a financial services company is designing a master data management solution for 'Product' data. The company has multiple source systems: Salesforce, a legacy ERP, and a product information management (PIM) system. The architect must ensure that the golden record for each product is always the most trusted version. Which factor is most critical when defining survivorship rules for product attributes?

Accepted Answer

The source system's authority for that specific attribute.. Survivorship rules must prioritize the source system that is most authoritative for each attribute. For product data, different systems may be authoritative for different attributes: the PIM for descriptions, the ERP for pricing. This attribute-level authority ensures the golden record contains the most trusted values. Recency, volume, or data type do not guarantee trustworthiness.

Answer

The recency of the attribute value across all source systems.

Answer

The number of source systems contributing to the attribute.

Answer

The data type of the attribute (e.g., text, number, date).

Question 8

A multinational retailer is consolidating customer master data from eleven country-level Salesforce orgs into a single global org. Each country org has its own account numbering scheme, and legal entities must remain distinguishable for tax reporting. Which MDM design should the architect recommend to reconcile the identifiers while preserving legal-entity separation?

Accepted Answer

Introduce a global master identifier and store each country's original account number as a cross-reference attribute on the account record.. Consolidating heterogeneous source systems calls for a neutral surrogate master identifier plus cross-reference attributes that retain each source system's original key. This avoids collisions between country numbering schemes, keeps political decisions out of the technical design, and preserves the traceability that tax reporting and reconciliation demand. Reusing one country's scheme or discarding legacy numbers both break auditability.

Answer

Create eleven separate account record types, one per country, and use the combination of record type plus the original country number as the composite key.

Answer

Use the Salesforce record ID generated on insert as the global identifier and discard the country-level numbers after migration.

Answer

Adopt the largest country org's account number as the global identifier and remap all other orgs' accounts to it during migration.

Question 9

A Salesforce architect is planning a migration of 2 million custom object records from a legacy Oracle database. The legacy system has a field 'Status' with values like 'Active', 'Inactive', 'Pending', and 'Archived'. In Salesforce, the Status field is a picklist with values 'Active', 'Inactive', and 'Pending' only. The architect needs to migrate the data while preserving as much information as possible and ensuring data quality. Which two actions should the architect take? (Choose two.)

Accepted Answer

Create a custom text field to store the original legacy status value for audit purposes, in addition to mapping to the picklist.. The architect should map the unsupported 'Archived' value to a valid picklist value like 'Inactive' to maintain data integrity and avoid load failures. Additionally, storing the original legacy status in a separate text field preserves the exact source information for auditing. This combination ensures data quality, traceability, and compliance with Salesforce picklist constraints.

Answer

Add 'Archived' as a new picklist value in Salesforce to accommodate the legacy data without transformation.

Answer

Use a validation rule to prevent 'Archived' from being loaded, and manually update those records after migration.

Answer

Exclude records with 'Archived' status from the migration to avoid picklist conflicts.

Question 10

A data architect is migrating 12 million Opportunity records into a new Salesforce org. The legacy system uses a custom 'Opportunity_Key__c' that must be populated for integration purposes. During a test load using the Bulk API in parallel mode, the team observes that some records fail with 'UNABLE_TO_LOCK_ROW' errors. What is the most likely cause of these errors?

Accepted Answer

Multiple batches in parallel are attempting to update the same parent Account records, causing row-level lock contention.. UNABLE_TO_LOCK_ROW errors during parallel Bulk API loads typically occur when concurrent batches attempt to update child records that reference the same parent records. Salesforce locks parent records to enforce referential integrity, and simultaneous access causes contention. Reducing parallelism or serializing the load for affected objects resolves the issue.

Answer

The custom 'Opportunity_Key__c' field is not marked as an external ID, preventing proper indexing and causing locks.

Answer

The parallel mode uses a single batch that is too large, exceeding the record lock timeout threshold.

Answer

The Bulk API parallel mode exceeds the daily API request limit, causing lock contention.

Question 11

A Salesforce org has a custom object Invoice__c with a Lookup relationship to Account. The business now requires that every Invoice__c record must always have a valid Account, and deleting an Account must also delete its related invoices. The architect decides to change the relationship type to Master-Detail. Which statement describes a valid consequence of this change?

Accepted Answer

The Account field on Invoice__c automatically becomes required, and the Invoice__c records are deleted when their parent Account is deleted.. Master-detail relationships enforce two key behaviors: the parent field is required, and deleting the parent cascades to delete the children. The scenario needs both a mandatory Account on every invoice and deletion of invoices when an Account is removed. Those requirements are satisfied only by the master-detail model, while lookup relationships leave the parent optional and do not cascade delete by default.

Answer

Invoice__c keeps its own sharing rules, and the Account lookup field must be manually marked as required in the field definition.

Answer

The Account field remains a lookup, but Salesforce automatically prevents deletion of an Account that has related Invoice__c records.

Answer

The Invoice__c object inherits the Account's sharing model, but the Account lookup field remains optional until a validation rule is created.

Question 12

A data architect at a global manufacturer is designing a master data management solution in Salesforce for customer accounts sourced from Salesforce, a legacy mainframe, and a partner portal. The business requires that the golden record reflect the most trusted source per attribute and that conflicts be resolved deterministically. Which two capabilities should the architect implement to meet these requirements? (Choose two.)

Accepted Answer

Define source ranking and attribute-level survivorship rules so that the highest-ranked source wins per field, with documented tie-breakers.. Deterministic, attribute-level golden records require two foundations: a consistent identity across sources and explicit trust ranking with survivorship rules. A global identifier and cross-reference table group all source records for the same entity, while source ranking with field-level survivorship and documented tie-breakers decides which value wins. Together they deliver the required trust and determinism; duplicate management, manual review, and external read-only access do not.

Answer

Use Salesforce Duplicate Management with matching rules and duplicate rules to identify and block duplicate accounts at entry.

Answer

Configure an external object via Salesforce Connect to read mainframe customer data in real time without replication.

Answer

Implement a data steward approval workflow that routes every field-level conflict to a human for manual selection before the golden record is written.

Question 13

A Data Architect is designing a data retention policy for a custom object that stores transaction records. The object has a master-detail relationship to Account and contains over 50 million records. The business requires that records older than 7 years be automatically deleted, but they must be archived first for compliance. Which approach should the architect recommend?

Accepted Answer

Use a scheduled batch Apex job that exports records to an external system and then deletes them from Salesforce.. A scheduled batch Apex job is the most appropriate solution because it can automate the export of old records to an external archive and then delete them from Salesforce. Batch Apex is designed for processing large data volumes and can be scheduled to run regularly. This approach ensures compliance with the retention policy and offloads data to reduce storage costs.

Answer

Configure a time-based workflow rule to delete records after 7 years.

Answer

Create a formula field that flags records older than 7 years and use a sharing rule to hide them.

Answer

Use the Data Loader to manually export and delete records every quarter.

Question 14

A Salesforce org has a custom object Case_Comment__c with 5 million records. The object has a lookup to Case. Users frequently run SOQL queries that filter by CaseId and OrderBy CreatedDate. The queries are slow. What should be done to improve performance?

Accepted Answer

Create a composite custom index on CaseId and CreatedDate.. When queries filter on one field and sort by another, a composite index covering both fields allows the database to use the index for both operations, avoiding expensive sorting and full scans. This is the most effective optimization for the given query pattern.

Answer

Create a separate custom index on CreatedDate only.

Answer

Use a formula field to combine CaseId and CreatedDate.

Answer

Enable skinny table for Case_Comment__c.

Question 15

A Salesforce org has a custom object Invoice__c with 8 million records. The business requires a dashboard that shows the total invoice amount grouped by Account and by Fiscal Year. The dashboard must refresh quickly, even during peak usage. The Invoice__c object has a lookup to Account and a formula field Fiscal_Year__c that extracts the year from Invoice_Date__c. What is the most appropriate design to support this dashboard efficiently?

Accepted Answer

Create a custom object Invoice_Summary__c that stores pre-aggregated totals per Account and Fiscal Year, and update it via batch Apex or scheduled flow when invoices change.. Pre-aggregating data into a summary object is the most reliable way to keep a dashboard fast when the source object has millions of records. By storing totals per Account and Fiscal Year, the dashboard queries a small, indexed dataset instead of scanning Invoice__c. Asynchronous maintenance via batch Apex or scheduled flow avoids impacting user transactions and keeps the summary current enough for reporting.

Answer

Enable Big Object indexing on Invoice__c and point the dashboard to a Big Object-backed report.

Answer

Build a custom Lightning Web Component that calls Apex to aggregate Invoice__c records on demand and display the results on the dashboard.

Answer

Create a summary report grouped by Account and Fiscal_Year__c, and add it as a dashboard component with a scheduled refresh.