Migrating a system like order capture to Salesforce raises three core confidence questions โ did every account transfer, do the counts match, and is referential integrity intact? This post covers two ETL Validator use cases that answer them: comparing data between a Salesforce org and an on-premise database to validate migration integrity, and baselining a product catalog or object metadata so any accidental changes to profiles, roles, or access privileges trigger automatic notifications to administrators.
Key Takeaways
- Migration confidence needs four checks: complete transfer, matching counts, integration accuracy, referential integrity.
- ETL Validator connects directly to Salesforce and on-premise DBs for count/record-level comparison, no custom scripting.
- Baselining protects catalog data โ snapshot + ongoing comparison flags unexpected changes automatically.
- Same approach covers metadata โ profiles, roles, and access privileges baselined to catch unauthorized changes per release.
Over the last few years, the Salesforce platform has become an incredible force in the market for various reasons. Of course, the most obvious use case is for the CRM capabilities. In addition, many organizations have started using the power of the force platform to build and deploy custom applications in the cloud at an incredibly fast pace.
Common Salesforce Data Testing Use Cases
Use Case 1: Comparing the data between a Salesforce Org and an OnPremise database.
Consider a simple order capture application that has been moved from an OnPremise to Salesforce. Also assume that the application has few basic objects; Account, Products, Order and Order Line Item tables. Now, after you move the data, few questions emerge:
- Did I get ALL the accounts from On Premise application to the Salesforce app?
- What is the best way for me to compare the counts?
- Are all the records between Salesforce and On Premise system matching from a data integration perspective?
- Is referential integrity between accounts, orders and order line items properly maintained in Salesforce?
These are simple questions but are extremely important to have confidence on the data migration process to the Salesforce platform. Using ETL Validator, you can easily create connections between Salesforce and your On Premise Database and execute the above tests in no time.
Use Case 2: Baselining the Product Catalog
Letโs say there are 1000 products in the catalog and it is important to ensure that the metadata of this product catalog does not get accidentally modified. How would you do that?
In ETL Validator, you can baseline a table and then run tests on an ongoing basis to ensure that the data accidentally does not get modified. If it does, then the platform can send out notifications with the records that do not have data as expected.
Use Case 3: Baselining Object Metadata โ Profiles, Roles, and Access Privileges.
Over a period of time, it is important to understand the changes to profiles, roles, access privileges etc in the Salesforce platform so that only the expected changes are going in with each internal release and nothing else is slipping through the cracks.
Using ETL Validator, you can take a baseline of the object metadata and then compare the same over time. If there are any differences, similar to the above use case, ETL Validator can send out notifications and alert administrators of unexpected changes.
To learn how to get started with Salesforce, you can check out the link below:
Conclusion
Moving business-critical data onto Salesforce โ whether itโs a migrated order capture app or ongoing metadata like profiles and access privileges โ doesnโt remove the need for validation, it just moves where that validation needs to happen. Comparing on-premise and Salesforce data for referential integrity, baselining a product catalog against accidental changes, and tracking metadata changes to roles and permissions are all recurring risks that manual spot-checks wonโt reliably catch at scale. ETL Validator addresses all three by connecting directly to Salesforce and running the same baseline-and-compare approach used elsewhere in the data stack, so unexpected changes surface automatically instead of silently making it into production.
Frequently Asked Questions: Salesforce Data Migration Testing
1) How do you validate a Salesforce data migration from an on-premise system?
ETL Validator connects to both the Salesforce org and the on-premise database to compare record counts, verify data integration accuracy, and confirm referential integrity is maintained across related objects like accounts, orders, and order line items.
2) What is baselining in the context of Salesforce data testing?
Baselining means taking a snapshot of a table โ such as a product catalog โ and running ongoing comparisons against it, so any accidental or unexpected data changes get flagged and trigger notifications.
3) Can ETL Validator detect unauthorized changes to Salesforce metadata?
Yes. By baselining object metadata like profiles, roles, and access privileges, ETL Validator can compare future states against that baseline and alert administrators when unexpected changes slip through with a release.
4) What Salesforce objects are commonly tested in a migration scenario?
Common objects include Accounts, Products, Orders, and Order Line Items โ testing focuses on confirming complete record transfer and correct referential relationships between them.
Rajesh Kumar A
Digital Marketing Manager, Datagaps
Digital Marketing Manager at Datagaps. Drives data-driven growth through content, performance campaigns, and marketing technology.
S P S Murthy Akella
Director, Technology Strategy, Datagaps
Director of Technology Strategy at Datagaps. Business solutions architect and Certified Scrum Master in data engineering, responsible AI, and ML across BFSI, telecom, aviation, and energy.
