The difference in the iData approach to other marketplace solutions is that by using the Kovenant™ methodology, we fix data quality issues first.
Once data is cleansed, we perform our transformation process, which benefits from iData’s highly collaborative and intuitive approach to mapping data.
Data mapping is one of the trickiest elements of any data transformation process, it's highly problematic when bringing business and technology teams together. To mitigate this, iData is able to make data mapping much more streamlined and visual to leverage business and tech teams' experience successfully.
Data mapping is a key part of feeding the approach to data transformations, like with data quality, the data mapping provides a clear indication of what the data transformations must look like in the target system.
In line with the migration process our Kovenant™ methodology executes and assures the transformation rules, using iData’s inbuilt data migration assurance engine. Using automation techniques to assure 100% of the data to find those needles in the haystack issues with the transformed and migrated data, including problematic transformation rules provides a rapid, repeatable way to ensure data migrations are successful.
Occasionally, transformation rules can be interpreted incorrectly, they may contradict other rules and key data may be migrated incorrectly or in some cases deleted without trace. Assuring two streams of data allows for it to be compared against each other and to create reports of any differences.
Multiple transformations can be applied to the data before comparison, so the raw data doesn't have to be identical to be successfully compared. This is particularly useful when comparing migrated data that has been transformed.