Recently the BBC posted this video. On first view it is just funny, but watching those dogs learn to drive really reminded me of personal experiences with IT teams making big learning transitions. To represent those real situations let’s consider a fictional team of SQL developers facing the daunting task of deploying a functional Hadoop-based analytics prototype in two months. The video parallels their critical learning success factors: (1) set audacious goals, (2) learn bit by bit, and (3) know your limits.
When Tom Petty sang, “Hey baby, there ain’t no easy way out” he wasn’t referring to business intelligence (BI) reporting but he might have been. Current generation reporting engines, AKA data visualization or data discovery tools, market their products with statements like these, emphasizing quick development and ease of use:
- “The democratization of data is here. In minutes, create an interactive viz (sic) and embed it in your website. Anyone can do it— and it’s free.” (Tableau Products Page)
- “Easy yet sophisticated report design empowers your employees to design professional and telling reports in minutes not days” (Windward)
I like these tools, and I do believe that they can provide a leaner, more productive, and more informative approach to BI reporting than some more mature products. However, none is a silver bullet for all data integration and reporting woes. Continue reading
In my experience, some BI projects ultimately finish as a success, but exceed budget and schedule targets and fall short of functional goals along the way. On projects like this, somewhere in the midst of report development, things get sticky and tasks fall behind schedule as the team runs into unexpected complexities. Continue reading
OK, I’ve lost a five-metre scrum, my pack has been overrun, and the ref has raised his arm between the sticks for a penalty try. My colleague Margy Thomas, with support of fellow rugger Billy Tilson, has convincingly argued that agile development in fact is very like rugby union. Margy cleverly fended my meager one-point case with a point-by-point list of the ways that agile projects and rugby are similar. I’ll hold on to my view that sports analogies are generally weak in describing application development, but I’ve come to observe a fundamental similarity between rugby and agile/scrum. Continue reading
What if you could double the efficiency of your software testing process, and substantially reduce errors found during the test, deployment, and maintenance phases, without purchasing any tool or method? The November 28 InformationWeek offers just that in a reprint of a recent Dr. Dobbs article on formal inspections by Capers Jones and Olivier Bonsignour. They call formal inspections the “defect removal tool of choice” and back up their claim with lots of hard evidence, but I think they are still selling short. Continue reading
I’m a data modeler, so I enjoyed Jonathon Geiger’s recent article entitled “Why Does Data Modeling Take So Long”. But why does he say it like it’s a bad thing?
Mr. Geiger’s bottom line is exactly right: “Most of the time spent developing data models is consumed developing or clarifying the requirements and business rules and ensuring that the data structure can be populated by the existing data sources.” On the projects he describes, no one took time before modeling to determine available data sources and identify business entities of interest, relationships among them, and attributes that describe them before database design started, so the data modeler had to do it.
I recently completed ScrumMaster training ably presented by Lyssa Adkins. Throughout the two-day class we appreciated Lyssa’s Zen-like, enabling, style. If her name is familiar, it’s because Ms. Adkins is the author of the book Coaching Agile Teams, one of the leading texts on the subject.
I’ve participated on agile projects, but so far only in a piggish/chickenish role, once in a three-week stint as a consulting architect and twice as the project manager serving as interface to the non-agile organization.
To me Ms. Adkins rocks at making students very introspective and critical of their past project experiences. These lessons stand out:
It is really bad, according to a recent survey by the Ponemon Institute (available here with registration). The white paper, entitled Health Data at Risk in Development: A Call for Data Masking, presents the results of a survey of 492 health care IT professionals on their companies’ practices regarding use of live personal health care data in application testing.
It makes a scary read. Here are the lowlights: Continue reading