Nine years ago when I started in the data integration and quality space, data quality was all about algorithms and cleansing technology. Data went in, and the “best” solution was the one that could do the best job of fuzzy matching the data and cleaning more data than the other products. Of course, not data quality solution could clean 100% of the data so “exceptions” were dumped into a file that were left as an “exercise for the user” to deal with on their own. This usually meant using the data management product of choice, when there is nothing else…. Data goes into a spreadsheet, and then users would remediate the mistakes by hand in the spreadsheet. Then someone would write an SQL query to write the corrections back into the database. In the end, managing the exceptions was a very manual process with very little to no governance to the process.
The problem with this of course is that for very many companies, data stewardship is not the person’s day job. So if they have to spend time checking to see if someone else has corrected an error in the data, or getting approval to make a data change, or spending time then consolidating all the manual changes they made and then communicating those changes to management, then they don’t have much time left to sleep, much less eat. In the end, but business of creating quality data just doesn’t get done, or doesn’t get done well. In the end, data quality is a business issue, supported by IT, but the business facing part of the solution has been missing.
But that is about to change. Informatica already provides the most scalable data quality product for handling the automated portion of the data quality process. And now, in the latest release of Informatica Data Quality 9.6, we have created a new edition called the Data Quality Governance Edition to fully manage the exception process. This edition provides a completely governed process for managing remediation of data exceptions by business data stewards. It allows organizations to create their own customized process with different levels of review. Additionally, it makes it possible for business users to create their own data quality rules, describing the rules in plain language…. no coding necessary.
And of course, every organization wants to be able to track how they are improving. And Informatica Data Quality 9.6 includes embeddable dashboards that show the progress of how data quality is improving and impacting the business in a positive way.
Great data isn’t an accident. Great data happens by design. And for the first time, data cleansing has been combined with a holistic data stewardship process, allowing business and IT to collaborate to create quality data that supports critical business processes.