Imagine one day you walk into the VP or Marketing’s office and you tell him, “Bob, we’ve suffered long enough, we need to clean up our data because we just can’t trust it anymore.” Bob looks at you with a blank stare and says, “What?” Then you say, “Yea, the data in our reports is incomplete, inaccurate, and out-of-date, and our analysis and decisions are suffering because of it. It’s a real mess.”

Unfortunately, this scenario is a reality for many organizations today. Bad data is simply putting business intelligence at risk. So the question is how do we make decision-making less of a gamble? The answer, ironically, is being discussed at SAP’s TechEd 2010 Las Vegas. Attendees at this conference over the past week have been sharing ideas about bringing confidence back to the decision maker – and leaving the gambling in the casino and out of the board room.

So how does one go about evoking trust in reports? Some data experts, like the ones presenting on Enterprise Information Management (EIM) in Las Vegas this week, would argue that a trend report on data should be served up next to every BI report – and here’s why. Trend reports graphically show how data quality is either progressing or regressing over time, through specific measurements. In parallel, BI operations are often run repetitively, on a regular schedule, with the results of the analysis published automatically. But what happens when some extraneous event causes the quality of the underlying data to degrade? How will the BI analyst know this? More importantly, when will the analyst know this, before or after the critical business decisions have been made?

That’s the first consideration. Get in a good habit of continuously monitoring the data to understand how the quality levels are changing. The next task is figuring out why those levels are fluctuating. Questions that will flow naturally out of that exercise of discovering that you have a data problem include; Where did the data come from? How was the data calculated? Were the business rules on the data applied correctly? Was the data cleansed and validated? By finding answers to these questions, you can begin to start fixing those data problems and apply a data quality process.

Is all the fuss really worth it? By monitoring the data quality levels of your reports, you are essentially beginning to treat your data as a strategic asset – which can be a huge competitive advantage. And by incorporating a data quality process within your data systems, sources, and applications – you prevent degradation on that asset. So, the next time you are faced with a decision, make sure it’s based on data you can trust, and reserve your ‘luck’ for use at the poker table. To learn more about SAP’s EIM solutions presented at SAP TechEd 2010 Las Vegas, check out the EIM Conference Track.   And visit www.sap.com/analytics/ for videos, collateral, and other related content.

Kristin McMahon
Enterprise Information Management
Director of Solution Marketing, SAP