Business Objects works… right? That seems to be the general consensus from its customers. Frank Dravis, back in 2005, wrote about categorizing data quality problems. In this blog he referenced what Professor Richard Wang, TDQM Co-Chair at MIT, calls the 15 dimensions of data quality problems (listed below).
Recently, DMreview.com reported that Business Objects sent “an apology to customers for issues related to poor service including delayed deliveries of the company’s technology.” When the technologies aren’t even available to its customers then these data quality dimensions are taken out of the equation… or maybe it adds one, “availability”; to be fair this is a problem and the business intelligence business is a business and customers are expected to receive what is promised to them.
After reading around a bit, it seems as though people thought the Business Object’s apology to its customers was a bit odd and unexpected but if we simplify the core of what is going on here, using a common metaphor as an example, it becomes clearer. Lets pretend you are a movie buff living in New York City. You have chosen the largest media provider available in Times Square as the place you always reserve your movies before they are released, specifically because they guarantee that you will get a copy. What happens when you show up to purchase that movie and the store doesn’t have it? You have an internal debate on whether or not to reserve movies from that particular store again while the manager gives you a formal apology.
In the end, unless I missed something, this boils down to a matter of credibility. Did this skew your view of Business Objects? Maybe. Maybe not. What I’m interested in now is figuring out how Business Objects ranks on the 15 dimensions of data quality. How would you rank Business Objects on the 15 points above?