I’m not one for making New Year resolutions; in fact as I told my father-in-law the other day, “I resolved to stop making resolutions a long time ago”. However I felt that from a professional perspective it makes sense to at least have some focal points for the year ahead.
From my point of view, 2011 was a pretty good year all things considered. There were plenty of ups and downs, both from the personal and professional aspects of my life but I think, in retrospect, the downs were outnumbered by the ups. Continue reading
One of the most frustrating questions I can hear as a data quality practitioner is simply two words; “so what?”
It’s not that it’s a difficult question to answer (although attributing costs and impacts can be challenging) it’s just that I can’t help but find this question at times a lazy and ignorant response to the raising of a data related issue. It often belittles a problem and inadvertently endorses a culture that is largely indifferent to data. Continue reading
In considering data as an organisational resource it is important to realise that it is quite different from other resources. Data is obviously not a tangible resource like product components in a manufacturing process; you can’t touch it or hold it however it does have the advantage of not depleting through use. You can use data and reuse it as much as you like and it will still be there for you to use again. This makes it a very valuable asset within a modern organisation but it also means that organisations can easily slip into bad habits that take data for granted. They forget that they have to put effort into nurturing their data in order to get the best out of it. You can take, take, take but if you don’t give in return then the effect on data, and consequently your organisation, can be disastrous. Continue reading
As part of my current role I’ve been heavily involved in the definition, documentation, and implementation of data quality rules as part of a Solvency II (Solvency 2) programme. One of the big challenges of this activity is being able to systematically manage and categorise rules and I thought that it might be helpful for others undertaking similar activities if I were to share the source of the method I chose to employ.
I’ve been reading Danette McGilvray’s excellent book, Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information, in which she uses the analogy of a Doctor utilising a “quick fix” to treat a patient rather than undertaking a thorough assessment, to help establish the importance of root cause analysis. This somehow got me thinking about Dr Gregory House; the main character in the television series ‘House M.D.’. What triggered the thought was the obvious doctor connection, but I started to think more about the way that ‘House’ undertakes his assessments. Continue reading