The goal of the Agile Data method is to describe a philosophical
foundation on which an effective approach to the data-oriented
activities on software development projects, and within IT departments,
can be based. First and foremost, the Agile Data Method subscribes to the values
and principles of the Agile Alliance. Although
this advice is a very good start, I believe that it needs to be extended with philosophies that
address the issues pertinent to the data community.
The Agile Data method is defined by its six philosophies:
An interesting observation is that most of these philosophies
aren’t specific to data, instead they are applicable to information technology
efforts in general. As the first
principle implies you need to look at the overall picture and not just data,
therefore data-specific principles very likely won’t serve you very well.
Heresy? No, just common
Data. Data is one of several important aspects of software-based systems.
Development teams must consider, and then act appropriately, regarding
enterprise issues. They need to take the bigger picture into account if
they're to avoid building yet another silo application.
Enterprise groups. Enterprise groups (such as
management, ...) exist to nurture enterprise assets and to support other
groups, such as development teams, within your organization.
These enterprise groups should act in an agile manner that reflects the
expectations of their customers and the ways in which their customers work.
Each development project is unique, as is each organization, requiring a flexible approach
tailored to its needs.
process does not fit all and therefore the relative importance of data varies
based on the nature of the problem being addressed.
IT professionals must work together effectively, actively striving to
overcome the challenges that make it difficult to do so.
You should actively strive to find the 'sweet spot' for any issue,
avoiding the black and white extremes
to find the gray that works best for your overall situation.