Leverage Data model patterns during Agile development to save time and build more robust applications."Get it done well and get it done fast" are twin, apparently opposing, demands.
The section ends with a perspective on t.
Other topics include industry models, iterative modeling, creation of patterns when none exist, and patterns for rules-in-data.
Consideration is given to the potential of enterprise views contributing to project-specific models.
The short-term "You Ain\'t Gonna Need It" (YAGNI) philosophy of Agile practitioners, and the longer-term strategic perspectives of architects, are compared and evaluated.
Creativity in Using patterns beyond their intended purpose is encouraged.
The second section, Steps Towards Data Agility, shares guidelines on generalizing and specializing, with cautions on the dangers of going too far. conceptual / logical / physical, and industry / enterprise / project), and you will learn how to customize patterns within specific model types. g.
A context of various types of Models is established (e.
As a starting point for resolving the differences, pattern levels of granularity are classified, and their interdependencies exposed.
The first section, Foundations for Data Agility, addresses some perceived aspects of friction between "data" and "agile" practitioners.
The three sections in the book provide guidelines for applying the lessons to your own situation, so that you can apply the techniques and patterns immediately to your current assignments.
If you need to deliver quality solutions despite exacting schedules, "The Nimble Elephant" will help by describing proven techniques that leverage the libraries of published Data model patterns to rapidly assemble extensible and robust designs.
Data architects are increasingly expected to deliver quality Data Models in challenging timeframes, and Agile developers are increasingly expected to ensure that their solutions can be easily integrated with the Data assets of the overall organization.
Leverage Data model patterns during Agile development to save time and build more robust applications."Get it done well and get it done fast" are twin, apparently opposing, demands
