Top 8 Data Quality Tools
SAP Data ServicesSAS Data ManagementSAP Information StewardInformatica Data QualityTalend Data QualityIBM Infosphere Information AnalyzerMelissa Data QualityOracle Data Quality
We can extract data at a table level, extract data at the ETL level, and we can extract data at an ODP level.
Data Services' table comparison mechanism is very powerful. It's pretty hard to find a similar feature in other solutions.
The tool is reliable, quick, and powerful.
The product offers very good flexibility.
The data profiling was excellent, as was the ease of generating the dashboards.
Very easy to deploy.
The user interface is flexible and the visibility of the data flow is amazing.
It is very useful for testing purposes and designing mappings for small projects. If you go for IDQ in the mapping itself, you can see the data. You can then correct it, and test it so easily. It is working fine. It is also stable, scalable, and easy to deploy.
The solution is customizable.
It is saving a lot of time. Today, we can mask around a hundred million records in 10 minutes. Masking is one of the key pieces that is used heavily by the business and IT folks. Normally in the software development life cycle, before you project anything into the production environment, you have to test it in the test environment to make sure that when the data goes into production, it works, but these are all production files. For example, we acquired a new company or a new state for which we're going to do the entire back office, which is related to claims processing, payments, and member enrollment every year. If you get the production data and process it again, it becomes a compliance issue. Therefore, for any migrations that are happening, we have developed a new capability called pattern masking. This feature looks at those files, masks that information, and processes it through the system. With this, there is no PHI and PII element, and there is data integrity across dif
Address parsing. Our other software does not have this functionality.
Getting the most up to date address for our members. We like to keep in touch with membership a few times a year so we want to maintain up to date addresses to be sure they receive any information that we mail to them.
I have found the most valuable features to be data cleansing and deduplication.
With Oracle Data Quality, the most valuable feature is entity matching.