SF-Data-Arch Data Migration Practice Question
A data architect is migrating 30 million Opportunity records into Salesforce. The legacy system has a 'Close_Date__c' field that is a date, but some records have invalid dates such as '0000-00-00' or future dates beyond 2099. The Salesforce Opportunity Close Date field is a standard Date field. The architect must ensure the migration does not fail due to these invalid dates. Which approach should be used?
⚠ Common exam trap
The trap here is assuming that invalid dates can be forced into Salesforce using truncation or default values, when the correct approach is to nullify and log them.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Load the invalid dates as NULL and log the affected records for manual review after the migration.
The architect should set invalid dates to NULL and log the affected records for post-migration review. Salesforce Date fields accept NULL values, so this prevents load failures. Logging allows for manual correction later, ensuring data quality without blocking the migration. This approach is scalable for 30 million records and maintains the integrity of the standard Close Date field.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Convert the invalid dates to a default date such as '1900-01-01' to maintain a non-null value.
Why it's wrong here
Using a default date like '1900-01-01' can distort reporting and analytics, as it does not represent the actual close date. It also may not be semantically valid for the business. While it prevents load failures, it introduces data quality issues that are harder to detect later. The better approach is to set invalid dates to NULL and log them for review, rather than populating misleading data.
- ✓
Load the invalid dates as NULL and log the affected records for manual review after the migration.
Why this is correct
Setting invalid dates to NULL prevents load failures because Salesforce Date fields accept NULL values. Logging the affected records allows for post-migration cleanup and manual correction. This approach balances data integrity with migration success, ensuring that valid records are loaded while invalid ones are flagged for review. It is a pragmatic solution for large volumes where manual correction before load is impractical.
- ✗
Create a custom text field to store the original date string and load it alongside the standard Close Date field, leaving Close Date blank for invalid records.
Why it's wrong here
This approach preserves the original data but adds unnecessary complexity and does not address the root issue of invalid dates. The requirement is to migrate into the standard Close Date field, not to create a parallel field. While preserving the original string can be useful for audit, it should be done in addition to, not instead of, properly handling the standard field. The load would still fail if invalid dates are attempted in the standard field.
- ✗
Use the Data Loader's 'Allow Field Truncation' option to bypass date validation and load the invalid dates as-is.
Why it's wrong here
The 'Allow Field Truncation' option is for text fields, not date fields, and does not bypass date validation. Salesforce will reject invalid date formats regardless of this setting. Attempting to load '0000-00-00' will result in a 'Invalid date' error. This option reflects a misunderstanding of Data Loader capabilities and Salesforce's strict date validation.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Salesforce exam blueprint
This SF-Data-Arch practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SF-Data-Arch exam.