Rittman Mead - Delivered Intelligence

Over at another Blog, Beth notes that she is editor of the month for the Carnival of Data Quality. When It comes out I urge you to take a look. With those strange quirks of global IT companies Beth and I once worked for the same employer, but we have never met - I did […]

A lot of data warehouses get some (if not all) of their data feeds through data files; in fact I can’t recall a recent project where at least one feed from an external system did not arrive as some form of flat file. I have had customers whose corporate data movement strategy is to go […]

My e-friend, Beth, has been busy posting from the Information on Demand conference in Las Vegas. She holds dear the belief that data is key, and quality data is the master key. I think saying it like that is putting words into her mouth, but hopefully I am not distorting her view point too much. […]

You’d almost think that Beth and I were the same person - we both seem to post about the same topics at around the same time. Today she posts on the joys of establishing standards in product descriptions, I had intended to write something similar, but instead I write this
Often the biggest problems in data […]

The other day a colleague invited me to sit in on workshop session with a customer to discuss changes to an attribute of product. On the face of it it sounds a bit of overkill to spend two hours discussing the meaning of just one attribute, but when that attribute is cost and the impact […]

Like buses in London you wait ages for one to arrive and then three come along at the same time. I started writing this piece a while back and since I started Beth wrote on data quality, Jon Mead touched on conformed dimensions in a follow up to his posting on dimensions, and Andy Whitehurst […]

As an acronym, GIGO for Garbage In, Garbage Out seems to have a better ring to it than the less common (or non-existent) terms TITO, RIRO or CICO. But the principle is the same; if you want good results, don’t store rubbish.
As I mentioned earlier we must guarantee the quality of our data. And to […]

The final installment on the ingredients for successful BI is about data quality. For some strange reason, if users do not trust the quality of data in a BI system the system will fall into disrepute and be seen as a failure. Now I said “strange reason” and in truth there is a degree of […]