Validating data migration

While data validation can be challenging, Alooma can help automate the process.Once you decide what data you want to validate and move, our data experts can help you plan, execute, and maintain your data pipeline.Data validation ensures that your data is complete (no blank or null values), unique (contains distinct values that are not duplicated), and the range of values is consistent with what you expect.Often, data validation is used as a part of processes such as ETL (Extract, Transform, and Load) where you move data from a source database to a target data warehouse so that you can join it with other data for analysis.In addition, Alooma specializes in securely moving your data so you can rest assured your data is safe. Alooma encrypts data in motion and at rest, and is proudly 100% SOC 2 Type II, ISO27001, HIPAA, and GDPR compliant. Enterprise tools have the benefit of being more stable and secure, but can require infrastructure and are costlier than open source options.

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However, after you have validated your data, a modern ETL tool such as Alooma can help you to expedite the process.The Python script can then take the XML as an input and process the results.However, this can be very time intensive, as you must write the scripts and verify the results by hand.This tool does not do any substantial validation of the data inside the files.

For example if you have a loan file for a patron who is not present in the patron file, these two files may still be considered 'valid' but the loan record will be rejected when the files are processed due to the lack of a linked patron record.If you have a large volume of data, you will probably want to validate a sample of your data rather than the entire set.

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