Agile Data

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The Agile Data (AD) method defines a collection of strategies that IT professionals can apply in a wide variety of situations to work together effectively on the data aspects of software systems. This isn’t to say that AD is a “one size fits all” methodology. Instead, consider AD as a collection of techniques and philosophies that will enable IT professionals within your organization to work together effectively when it comes to the data aspects of software-based systems.

Modern software development processes - such as Disciplined Agile Delivery (DAD), Extreme Programming (XP), and Scrum -- are all iterative and incremental (evolutionary) in nature. Every single one of them. Some modern approaches, in particular XP and Scrum, are agile in nature (for the sake of simplicity, let's define agile software development as a highly collaborative and evolutionary approach). Traditional approaches to the data-oriented aspects of software development, however, tend to be serial, not evolutionary and certainly not agile, in nature. This is a serious problem.

Data has been an important aspect of every single business application which I have ever built. Then again, so have business rules, user interfaces, networks, and a slew of other issues. My experience is that left to their own devices software developers will usually struggle to get the data stuff right, and will often make questionable decisions from an enterprise data point of view. My experience is also that many data professionals are difficult to work with, often because they are stuck in their "serial ways" but also because they have little or no experience following modern software development techniques. These two observations reflect the cultural impedance mismatch between the two groups, a problem which is often over-shadowed by the technical impedance mismatch between the two technologies (object-based and relational) which the two groups work with.

Important Topics in Agile Data

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