If your data warehouse server(s) burned up in a fire, how long would it take to redeploy the system into production?
If you discovered a critical defect in your production BI system, how long would it take to revert to a previous version while you resolve the problem?
Like other mission critical systems, it should take no more than a few days to rebuild your BI system from scratch – including reconfiguring new servers and reloading data. The actual redeployment of your warehouse implementation (database schemata, ETL scripts, BI applications, etc.) should range from minutes to hours, not days or weeks. Continue reading “BI System Version Control and Code Management” »
Remember that our goal in agile BI development is the frequent release of production quality working software for user feedback and acceptance. At the end of each iteration or sprint, and each release our working product is expected to be of shippable quality, even in its most embryonic stages. This objective requires an entirely different approach to our quality assurance methods. Foremost it means integrating QA efforts right into our iterations.
Traditional BI development methods push system and acceptance testing to the end of the project cycle. This backend testing is typically manually intensive, possibly supplemented by the use of semi-automated tools. We need an entirely different testing discipline for Agile BI development. Continue reading “Automated Data Warehouse Testing” »
Contrary to popular opinion, the best business intelligence systems are not driven by the data, or the operational source systems. I recently had a conversation with a group of data warehouse developers who were completely baffled by the notion of building a BI application without first extracting all of the source system data into a single, normalized data model.
I occasionally get asked to describe agile project failures and struggles. I haven’t formally studied root causes of failure but have worked with enough struggling agile teams to gain a qualitative sense of these causes. Agile struggles are commonly caused by non-agile behaviors masked behind agile trappings and terminology. Failure to collaborate is a common problem. People tend to revert to the asynchronous communication (e-mail and written documents); and “throw-it-over-the-wall” habits with which they’ve grown familiar. Continue reading “On Community, Customers, and Collaboration” »
In 2006 NBC launched a television series in the U.S.A. called Studio 60, a comedy/drama about the production of a weekly live variety show ala Saturday Night Live. The series gave viewers a behind the scenes look at the intensity with which each new weekly variety show is planned and executed. Unlike typical weekly TV shows, each episode of a live variety show is planned in a “just in time” fashion. The content must be adapted to current events, the decisions of producers must be responded to immediately, and the cast and crew must be highly adaptable to change. No matter what happens during the week, the show must be completely planned and ready to air at a fixed time. And it must be good enough every week to keep viewer ratings very high or risk cancellation. Imagine the pressure!
So here is a summarization of the key characteristics of Agile BI. This is simply a high level glimpse at the key project traits that are the mark of agility; not an exhaustive list of practices. Moreover, Agile BI is a development style not a prescriptive methodology that tells you precisely what you must do and how you must do it. The dynamics of each project within each organization require practices that can be tailored appropriately to the environment. Remember, the primary objective is a high quality, high value, working BI system. These characteristics simply serve that goal:
Business intelligence systems are complex and dynamic organisms that require a lot of care, feeding, and proper upbringing in order for them to contribute value back into the organization. In fact, they are a lot like our children, who require constant nurturing to grow into the mature and contributing adults that we hope they will become. At birth, a BI system represents a vision of what it will someday become. This vision is a collection of the wishes and dreams of key stakeholders based on current issues and needs. Just like the visions and plans of young inexperienced parents, these issues and needs change over time, and so do stakeholder visions. As the system matures it must adapt to these changes in order mature into a relevant and valuable business intelligence solution. Continue reading “Agile BI: Raising Your Baby to Adulthood” »
I’ve been reflecting a bit on my Cutter 2010 prediction – “Although Agile adoptions will proliferate, we will see an increase Agile project failures due to misunderstanding, misapplication, and misguided attempts to follow an ‘agile recipe’.” It feels a little pessimistic to me so I wanted to elaborate further and hopefully give readers some ideas about how to avoid experiencing an agile failure. As an agile consultant I get to work with a lot of different companies in various stages of agile transformation; with varying corporate cultures; and experiencing varying challenges and successes. Through these experiences success patterns and anti-patterns emerge. Continue reading “Adapting is Key” »