Let’s look at some statements:
• Business Intelligence and Data Mining is based on looking into historical data in order to make better decisions for the future.
• Some of the best results from Business Intelligence and Data Mining are made when looking at data in different ways than done before.
• It’s a well known fact that Business Intelligence and Data Mining is very much dependent on the quality of the (historical) data.
• We all agree that you should not start improving data quality (like anything else) without a solid business case.
• Upstream prevention of poor data quality is superior to downstream data cleansing.
• The business case can’t be established before we start to look at the data in the different way.
• Data is already stored downstream when that happens.
• Anyway we didn’t know precisely what data quality issues we have in that context before trying out new possible ways of looking at data.
Solutions to these timing issues may be:
• Always try to have the data reflect the real world objects they represent as close as possible – or at least include data elements that makes enrichment from external sources possible.
• Accept that downstream data cleansing will be needed from time to time and be sure to have the necessary instruments for that.