This week I was lucky enough to attend the New Zealand Identity Conference 2012: Managing Digital Identity in a Networked World. Organised by the Victoria University of Wellington, School of Government; The Office of the Privacy Commissioner; and the Department of Internal Affairs, it was held at Te Papa (The Museum of New Zealand) and pulled together identity and privacy experts from New Zealand and the rest of the world. I found it very interesting and valuable, so I just thought I’d post an overview here, and then explore thinking inspired by the conference in other posts.
A recent article on ReadWriteWeb reminded me of one of the more annoying sources of noise about cloud computing – the double standards of US government agencies and companies around cloud data residency. On the one hand US government agencies complain that other countries are discriminating against its cloud service providers by raising legitimate concerns about data privacy in the US, while at the same time as making Google create special government clouds which keep all data in the US.
Talking and listening to Jim Harris of OCDQ Blog has got me thinking about data management. Specifically I’m thinking about the challenges facing data management in the New Zealand government sector – where I currently work. Initially when I started here, and saw some issues relating to data management, I thought: “yep, I’ve seen this before – the issues and the answers are the same as in the private sector.” Now that I have been working here a bit longer, I realise that this is only half right, that there are some issues that are specific to government (or the New Zealand government) and that some solutions common in the private sector cannot be straightforwardly applied here either.
One of the significant challenges facing data management in government is navigating the restrictions and constraints introduced by privacy legislation. Why does this matter and how does it impact data management? Well, to take just one example: you can’t create a single view of a customer (or citizen) if the interpretation of privacy law is that you aren’t allowed to match pieces of information about the same person if they are obtained for different purposes. I thought I’d write a series of short posts on this topic, starting with this one on why privacy is a bigger issue for government agencies than it is for the private sector.
In an earlier post I raised the question of “what is sexy billing?” That is: what would an organisation’s billing capability look like if it was regarded as positive and desirable rather than negative and boring? This was based on assumptions about what “billing” was – an assumption questioned in the comments. So I then wrote a post describing what I thought “billing” meant. This in turn raises questions about what a bill really is, which I will attempt to answer here.
I have recently discovered the podcast on data quality (and related matters) called OCDQ Radio. It is part of the OCDQ Blog “empire” (term used advisedly!) run by Jim Harris. What does “OCDQ” stand for? Well: Obsessive-Compulsive Data Quality, which pretty well describes Jim and his attitude towards data quality and other things data related. OCDQ Radio is exactly what I like in an enterprise IT (for want of a better label) podcast. The podcasts are in-depth examinations of particular topics related to data quality (the episodes on identity matching and master data management were particularly good). They give you a decent introduction to a topic, and then follow that up with a closer examination of specific issues in that area. If you are interested in data quality in the enterprise, and in understanding the different technologies and methods for improving it, then I would recommend you listen to this podcast.
OCDQ Radio on iTunes.