The Importance Of Developing A Data Quality Checklist

The Importance Of Developing A Data Quality Checklist

In modern businesses, maintaining control over a company’s performance often boils down to maintaining control over its data. When used and interpreted correctly, data tells you everything you need to know to judge your company’s current state and plan its next move. Of course, your conclusions will only be wise if you can trust the data you’re working with; this makes it important to develop workable data quality checklist.

Why Data Quality Management Matters

As information technology grows more capable and penetrates every facet of the business world, a lot of organizations find themselves positively swamped by more data than they know how to handle. The reluctance to ignore or discard any data often leads to the introduction of inaccurate, obsolete, or duplicate data into your company’s records.

This poses a serious problem when you attempt to manipulate your data and draw conclusions from the process. Profitable departments can look like loss-leaders and productive processes can appear to be idle if you’re looking at inaccurate data. Smart business leaders get out in front of this problem and establish forward-thinking plans to clean up their data and ensure it remains accurate in the future.

Important Items Your Data Quality Checklist Must Address

The potential problems discussed above should give you a rough idea of the concerns your data quality checklist needs to address. For every individual record you maintain, there are some basic questions you need to ask: Is the record accurate? Does it conform to the proper format? Is it unique? Is it up-to-date?

Besides showing the tests you need to subject your records to, your checklist should also point the way towards correcting errors. Each item on your checklist should come with a fixed procedure for dealing with any record that fails the item. By carefully refining a checklist that works for your organization, you should be able to kick off a continual process of data quality improvement.

Strategic Vs. Tactical Checklists

In the same way that you can apply a checklist to individual records, you can also use the checklist methodology to guide your data management process as a whole. Any company of sufficient size will require continuous data management to keep its records clean and deal with changing priorities and requirements. However, you don’t always have the resources necessary to handle all of your data management work at once.

Checklists will help you keep your data quality priorities straight. You can use them to construct an effective long-term plan for maintaining and improving the quality of your data. A strategic data quality checklist should be a living document, though! Don’t be afraid to alter your plans when your goals shift.

Data management is a big job, and it’s only going to get more important in the future as technology advances further. Take the lead sooner rather than later and use smart management techniques — like quality checklists — to ensure that your company keeps its important data as accurate and useful as possible.