During conference season, it can be a challenge to come up with abstracts that you can feel passionate about, while making sure to craft them in a way that is both attractive to selection committees and the audience you feel like you want to reach. I often find that tri-purpose (satisfying myself, a committee, and the potential audience) to be daunting and occasionally conflicting — leading to abstract paralysis.
Starting today, I’m going to work harder at it. If you’ve been to any of my presentations in the recent past, you know that I like to spend more time on what I think are technical “culture” issues rather than examples of how to implement or interpret the technical features of the latest software release. It’s an area that I’m passionate about, and it’s one that I feel is drastically underrepresented and underserved at most technical conferences.
The biggest challenge I have with those kinds of presentations is making them selectable and attractive — for the topics mostly concern our ability to collaborate and communicate effectively in support of our business and mission objectives. And in that case, we all feel (myself included) like we’re from Lake Wobegon.
To me, no where is this more apparent than in the discussions about the Agile movement in software development, testing and production operations. Fellow Oak Table member Martin Widlake has some excellent examples of these issues in his 2 recent blog posts on the subject:
(I especially like “Ilk”)
In a small, forgotten corner of the Internet, I belong to a Yahoo! Group (yes, they still exist!) on Agile Databases, which has as its description:
Discussion about Database management with regards to Extreme Programming practices and principles.
You can visit the group here.
In a recent discussion, there was a post from Scott Ambler that I found myself violently agreeing with:
A question was asked about coordinating and scheduling changes made by database and ETL teams with the development teams in order to reduce confusion and churn during development.
Question / Comment: While one or more code iterations are taking place in parallel, the data design and ETL are working on their iteration of the db schema and data, which will be consumed by later code iterations.
Scott’s Comment / Answer: Better yet, this could occur in a “whole team” manner where data-experienced people are embedded in the actual team. This can improve productivity by reducing overall overhead. Unfortunately this can be difficult in many companies due to the organizational complexities resulting from the cultural impedance mismatch between data and development professionals.
I feel like I’ve have the privilege of working in places where those organizational complexities and cultural impedance mismatches were overcome and I’d love to talk about what I think made that happen.
Now just to write some compelling abstracts on the subject — ideas welcome!