Data Validation roundCorner

by Stephanie Buckwalter and Chris Ojeda

To paraphrase Chris on a client call the other day, “It is all well and good for us to tell you the data has been loaded correctly–but you need to validate to know the data is true.”

To his point, roundCorner does provide validation of data that we migrate. Our Data Specialists confirm that numbers match up and that information is loaded into the correct fields based on mapping sessions with the client. They also review, diagnose, and help resolve any error files.

At the same time, nobody knows your data like you do. 

Yes, Data Specialists can check if data was loaded successfully. But they cannot know if there were any issues or inconsistencies with the source data. Certainly, Data Specialists can validate the correct mapping of data points based on mapping discussions. However, they cannot know if the data looks and feels right since migration took place.


“It is all well and good for us to tell you the data has been loaded correctly–but you need to validate to know the data is true.”

Data Validation Up Front

You must not wait to validate your data after it has migrated to your production instance. Spend the time up front to have some power users or SMEs work on the data validation. This will pay off tremendously when your end-users enter the system for training or go-live and find clear, clean data.

Initially, roundCorner delivers and executes the migration process against your sandbox instance of NGO Connect (NGOC). At this time, both parties review the source data mappings and how the migration affects other fields in NGOC. These fields include summary fields and ownership. After discussing any discrepancies and making adjustments to the migration process, we can perform additional iterations of migrated data. This may reveal issues with the source data that we can address and also refresh. As a result, the migration can provide the best possible outcome of clean and accurate data.

In addition to the above, data validation will help provide confidence in the data migrated to your production instance. Even if there needs to be tweaks to the data, staff will feel empowered to take part in the process. What could be an intimidating transition to some users will now be a bit less so.

Observing Migrated Data

It is important to look at your migrated data in a variety of ways.

Certainly, you want to validate that the numbers of records looks correct. You also want to look at specific field mappings to confirm accuracy. However, you want to look at some records holistically. It is key for the involved users/testers to identify a set of records with which they are very familiar (often high dollar donors), and records that have some complexities as well. Since this set of records is so familiar to the team doing testing, it will be much easier for them to identify any concerns.

Furthermore, it is important to know that the data may not exactly match the old data schema, and “totals” can be slightly different. In addition, the user needs to understand that values may be counted in different buckets as part of the mapping process.

Learn More

Still have questions about data validation at your organization? Contact us.

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