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SmartData Collective > Uncategorized > Get Smart about Your Data Quality Projects
Uncategorized

Get Smart about Your Data Quality Projects

SteveSarsfield
SteveSarsfield
5 Min Read
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With all due respect to Agent Maxwell Smart, there is a mini battle between good and evil, CONTROL and KAOS, happening in many busy, fast-growing corporations. It is, of course, with information quality. Faster growing companies are more vulnerable to chaos because by opening up new national and international divisions, expanding through acquisition, manufacturing offshore, and doing all the other things that an aggressive company does, it leads to more misalignment and more chaotic data.

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 …


With all due respect to Agent Maxwell Smart, there is a mini battle between good and evil, CONTROL and KAOS, happening in many busy, fast-growing corporations. It is, of course, with information quality. Faster growing companies are more vulnerable to chaos because by opening up new national and international divisions, expanding through acquisition, manufacturing offshore, and doing all the other things that an aggressive company does, it leads to more misalignment and more chaotic data.

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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.

Covering the world of data integration, data governance, and data quality from the perspective of an industry insider.

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