SF-Data-Arch Data Migration Practice Question
What is the primary benefit of performing a data cleansing exercise before initiating a migration to Salesforce?
⚠ Common exam trap
Candidates often underestimate the cost of post-migration cleanup. They wrongly assume that fixing data inside Salesforce is easier than cleaning it beforehand, ignoring the complexity of existing business logic and dependencies.
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
✓
It prevents the migration of invalid or duplicate data into the new system.
Data cleansing is the process of detecting and correcting corrupt or inaccurate records. Doing this before migration is vital because it prevents the 'garbage in, garbage out' syndrome. High-quality data ensures that the new system is reliable from day one, improves user adoption, and prevents the need for costly post-migration data remediation projects which are significantly more complex once the data is integrated into existing business logic.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
It eliminates the need for field mapping in the ETL process.
Why it's wrong here
Data cleansing does not replace field mapping. Mapping is the technical process of connecting source fields to target fields, while cleansing is the qualitative process of ensuring the data within those fields is correct. You still need to map the fields regardless of the data quality state.
- ✗
It ensures that the target Salesforce Org meets storage limits.
Why it's wrong here
While removing unnecessary data reduces storage usage, the primary benefit of cleansing is data accuracy and system reliability. Storage management is a secondary benefit. The main goal is to avoid migrating invalid, duplicate, or obsolete data that would negatively impact business operations within the new Salesforce environment.
- ✓
It prevents the migration of invalid or duplicate data into the new system.
Why this is correct
Cleansing removes inconsistencies, duplicates, and inaccurate values. By doing this early, you ensure the new Salesforce system is populated with high-quality, trusted data. This is essential for successful adoption and reporting, as users are more likely to trust the system when the records are clean and reliable.
- ✗
It automatically adjusts the Salesforce schema to fit the legacy data.
Why it's wrong here
Cleansing the data does not modify the Salesforce schema. The schema must be built based on business requirements, and the data must be transformed to fit that schema. Cleansing is about correcting the data content, not changing the target system's database structure to accommodate messy source data.
About these practice questions
This SF-Data-Arch question is part of Courseiva's 222-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
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.