Since engaging in the social media community around data and information quality I have noticed quite a lot of mobbing going on pointed at data quality tools. The sentiment seems to be that data quality tools are no good and will play only a very little role, if any, in solving the data and information quality conundrum.
I like to think of data quality tools as being like the cygnet (the young swan) in the fairy tale “The Ugly Duckling” by Hans Christian Andersen. An immature clumsy flapper in the barnyard. And sure, until now tools have generally not been ready to fly, but been mostly situated in the downstream corner of the landscape.
Since last September I have been involved in making a new data quality tool. The tool is based on the principles described in the post Data Quality from the Cloud.
We have now seen the first test flights in the real world and I am absolutely thrilled about the testimonial sayings. Examples:
- “It (the tool) is lean”. I like that since lean is a production practice that considers the expenditure of resources for any goal other than the creation of value for the end customer to be wasteful.
- “It is gold”. I like to consider that as a calculated positive business case.
- “It is the best thing happened in my period of employment”. I think happy people are essential to data quality.
Paraphrasing Andersen: I never dreamed there could be so much happiness, when I was working with ugly ducklings.
Liliendahl on Data Quality 
Sounds like a great data quality tool you are working on. Does it have a name yet? Or haven’t you decided between Cygnet and Ugly Duckling? 🙂
When do you take it out of the “cone of silence”? Is it focused on customer and address remediation or is it more generic? Will there be a beta program? Any press releases you can share again?
Thanks, Gordon
Thanks for asking Gordon.
The tool is called iDQ – short for instant Data Quality.
The current version is aimed at party master data (customers/prospects, suppliers and employees). For now we offer external data sources available in Denmark (some information available in Danish here).
The unique feature is how multiple external sources are searched and presented along with internal data during data entry and how data capture may initiate ongoing maintenance of data.
Though the current scope is limited we have great ideas on how to embrace world wide data, social media sources and other entity types.
Henrik,
Congrats on the birth of your new “baby”.
It really sounds exciting! Sounds like you’re pushing data quality verification upstream – where it should be – at data entry.
Looking forward to hearing more about this – for the global market.
Rgds Ken
Thanks Ken. Yes, world dominance is of course the end goal 🙂