While a company may have a strong desire to “own the world” or at least their market, they may wind up owning chaos and disorder instead – in the form of disparate data. The challenges include:
- trying to reconcile technical data quality issues, such as different code pages like ASCII, Unicode and EBCDIC
- dealing with different data quality processes across your organization, each that that deliver different results
- being able to cleanse data from various platforms and applications
- dealing with global data, including local languages and nuances
Agent 99: Sometime I wish you were just an ordinary businessman.
Maxwell Smart: Well, 99, we are what we are. I’m a secret agent, trained to be cold, vicious, and …
While a company may have a strong desire to “own the world” or at least their market, they may wind up owning chaos and disorder instead – in the form of disparate data. The challenges include:
- trying to reconcile technical data quality issues, such as different code pages like ASCII, Unicode and EBCDIC
- dealing with different data quality processes across your organization, each that that deliver different results
- being able to cleanse data from various platforms and applications
- dealing with global data, including local languages and nuances
Agent 99: Sometime I wish you were just an ordinary businessman.
Maxwell Smart: Well, 99, we are what we are. I’m a secret agent, trained to be cold, vicious, and savage… but not enough to be a businessman.
In an aggressive company, as your sphere of influence increases, it’s harder to gather key intelligence. How much did we sell yesterday? What’s the sales pipeline? What do we have in inventory worldwide? Since many company assets are tied to data, it’s hard to own your own company assets if they are a jumble.
Not only are decision-making metrics lost, but opportunity for efficiency is lost. With poor data, you may not be able to reach customers effectively. You may be paying too much to suppliers by not understanding your worldwide buying power. You may be driving your own employees away from innovations, as users begin to avoid new applications because of data.
KAOS Agent: Look, I’m a sportsman. I’ll let you choose the way you want to die.
Maxwell Smart: All right, how about old age?
So, it’s up to data quality vendors to provide solutions to help high-growth companies “get smart” and defeat chaos (kaos) to regain ownership of their companies. They can do it with smart data-centric consulting services that help bring together business and IT. They can do it with technology that is easy to use and powerful enough to tackle even the toughest data quality problems. Finally, they can do it with a great team of people, working together to solve data issues.
Agent 99: Oh Max, you’re so brave. You’re going to get a medal for this.
Maxwell Smart: There’s something more important than medals, 99.
Agent 99: What?
Maxwell Smart: It’s after six. I get overtime.
