How to Fix Bad Data

Beth Adams's picture
 By | mei 03, 2017
in iWay , Omni, Omni-Gen, Data Quality, master data management
mei 03, 2017

Do you realize that poor data quality can be a costly problem for you and your organization, even if you don’t see any data integrity problems? Consider that data cleansing can actually be good for your budget.

When you manage data quality early in its lifecycle, it’s cheaper and more effective than going backward and fixing what has already been delivered.

If you put your IT department in charge of your entire data quality strategy, without heavy involvement from business users and executives, you may want to rethink your plan. Economically, it’s a better bet to have your organizational culture include all players – IT and business people alike – in the data quality process.

To get support for your program, build a business case that includes all of the stakeholders in your company who would need to approve a strategic data quality plan. But realize that that’s only the start. You need to present your case consistently and repeatedly to get the required funding.

We have a client who improved data quality by developing and implementing a strategic data management plan involving their entire organization. The Kansas City Police Department (KCPD) needed to bring together and streamline data from more than 27 sources. As the 32nd largest police department in the nation, KCPD helps protect 464,000 residents across 322 square miles.

KCPD used records from many departments that were supplied in various formats. Working as a team, they standardized the information for consistency in order to make it readily available. Using our data quality software helped them to create golden records – particularly helpful when suspects and criminals use aliases, so they can have one record per person, no matter the name used.

Our new SlideShare gives a great visual example of how fixing bad data goes a long way to helping your organization.

And see more practical advice on fixing bad data and best practices by reading our new white paper “The Real Cost of Bad Data: Six Simple Steps to Address Data Quality Issues”, and let us know what you think.

Happy spring cleaning!