Data quality is an ever-present enemy of business applications and database systems. Sure, the data may be accurate today, but things change. And when they do, how quickly can you adapt? How do you even find out that things have changed?
65.8% of business cards will have a title and/or job function change within a year. Think about this in context of your marketing database! Given such a rapid rate of change, how can we ever hope to have 100 percent accurate information in our databases?
The short answer is “we cannot!” But that doesn’t mean we shouldn’t keep striving for that elusive goal. How can you ensure that you and your organization are “fighting the good fight?”
Well, you can start by ensuring that your organization embraces data governance. Why do we govern anything? Basically, it is to balance human self-interest with the common good. This is why countries create a government, right? So data governance is there to balance the general impulse of creating data willy-nilly and copying it everywhere without any definition or control against the common good of well-defined data of high quality. Sounds good, right?
Another implication of governance is that the whole organization is involved. Governance is about organizational behavior. Contrast that with data administration which is usually controlled by a small group within IT that tries to involve business users with varying degrees of success.
Additionally, you can purchase and adopt some of the many software tools available today to assist in defining, securing, controlling, and managing data. Or course, tools alone will never be sufficient. The tools have to be used practically and efficiently within an organization that embrace data governance.
A big part of this is treating data as the corporate asset that it undoubtedly is. But, although many organizations say they do this, few actually do. Just about every high level executive mouths the platitude that they “treat data as a corporate asset .” But think about how we treat other important assets. Our finances, that is, monetary assets, are treated much more rigorously than we treat data. If our financial statement is one penny out of balance we will not stop working until we track it down and get it right. Do we do the same thing for data quality? What about human resources? Every company has an organization chart that maps their personnel to their department and job. Do we have a corporate data model to accomplish the same task for our data? No, we do not treat data like we treat other assets, at least not yet.
The data is decaying and for the most part, we are ignoring that fact. And how can you ever hope to succeed as a business with bad data?