Join IDERA and Joseph Maggi while he discusses some of the more heated debates in the data modeling world centered around the concept of agile data modeling. Much of this debate has its roots in a misunderstanding or at least conflicting views on what Agile is in the first place. Some view agile data modeling as a haphazard approach to database “design” while others view it as a way to get applications developed more quickly and efficiently. This session will explore the merits of both sides of the argument and will discuss the technical manifestations of Agile (namely Scrum and Kanban) and where data modeling fits within these agile methodologies.
You can view the slide deck here and the webinar recording here.
Thank you for providing suggested agile frameworks for Data management/data warehousing projects. Currently I follow the scrum/sprint methodology for data modeling stories, we do run into issues when I trying to complete the modeling stories within the 2 week sprint. The reason could range from time taken to do data profiling, data analysis, understanding business context of the data element or identifying a subject matter expert. This leads sometimes splitting of stories , which in turn ends up turning stories into more waterfall like tasks. Should kanban method be considered in such cases.
In reply to ramdas2016:
In reply to Joseph Maggi: