A month ago I made a blog post titled “Data Quality and climate politics”. In this post I highlighted some similarities between data governance / data quality and climate politics mainly focussing on why sometimes nothing is done.
Today, 1 day before the United Nations climate change summit commence in my hometown Copenhagen, it seems that executive buy-in has come through. Over 100 heads of states and government will attend the conference among them key stake holders as Indian prime minister Singh and US president Obama.
The plan for how to manage climate change seems at this moment to have some ingredients with similarities to how to manage data quality change.
Related to my previous post Eugene Desyatnik commented on LinkedIn:
In both cases, everyone in their heart agrees it’s a noble cause, and sees how they can benefit — but in both cases, everyone also hopes someone else will pay for most of it.
Progress in fighting climate change seems to be closely related to that the rich countries seems to be in agreement about paying a fair share.
With enterprise data quality you also can’t rely on that one business unit will pay for solving all enterprise wide data quality issues related to common data domains.
Key Performance Indicators
Reductions in greenhouse gas emissions are key performance indicators and goals in fighting climate change – measuring temperatures is more like looking at the final outcome.
For data quality we also knows that the business outcome is related to information in context but in order to look at improving progress we have to measure (raw) data quality at the root.
This article from BBC “Tackling climate change with technology” points at a wealth of different technologies that may help fighting global warming while we still get the power we need. There is pros and cons for each. Some technologies works in some geographies but not somewhere else. Some technologies are mature now and some will be in the future. There is no silver bullet but a range of different possibilities
Very similar to data quality technology.