20. May 2008 by Rick Abbott.

Data Quality - everyone wants it, and everyone complains that they don’t have “good quality data”.  But how do you define data quality? What are the business benefits associated with the investment required to improve the quality of corporate data? Those are the questions you should be asking when approached by an angry business user complaining they can’t do their job because their data source(s) stink.

I think the most common misconception around DQ is that it’s an all or nothing proposition.  In reality there’s a cost-benefit analysis required to determine the payback associated with improving data quality.  Raising the data quality bar has a cost, and unless you can justify the expenditure you’re wasting corporate resources.

The business case can range from a simple exercise in comparing the cost of automating vs the current cost of manual labor required to fix and/or circumnavigate around incorrect data elements.  For example, it doesn’t make sense to spend a half million dollars implementing a data quality technology solution, to save a couple of hours a week of a business or data analyst’s time.  On the other end of the spectrum are strategic implications such as financial reporting and risk management, where the reputation of the company is at stake (just ask Fannie Mae).

Look at data quality as a bar that you raise and lower based on cost, business benefit, risk tolerance, and other factors that are important to the corporation.

Posted in Industry Buzzwords | 1 Comment »

20. May 2008 by Rick Abbott.

The term “Business Intelligence”, or just BI, has been used and abused so much that it has nearly as many personalities as Herschel Walker.  And that’s just within the context of the analytics and data management community, never mind the legions of people who associate it with corporate espionage.

Within the analytics world, BI has taken on (at least) the following definitions:

• The process of utilizing data for making better business decisions.  Sometimes used interchangeably with business or corporate performance management (originally coined by Gartner analyst Howard Dresner) 
• Reporting and dissemination of data from a data warehouse
• All systems required for collecting, integrating, cleansing, and reporting of data
• Software tools that extract data from a repository (database or otherwise) and present to a user in various formats
• Metrics used to measure business performance

So when someone uses the term BI, make sure you understand the context of the discussion (and the person’s background) so you’ll know which alter ego you’re conversing.

Posted in Industry Buzzwords | 1 Comment »