John Giles Livres

THE DREAM WAS FOOTBALL . . .

Leverage data model patterns during agile development to save time and build robust applications. The demands of delivering quality solutions quickly create challenges for data architects and agile developers. This resource offers proven techniques to utilize published data model patterns for assembling extensible designs efficiently. The book is divided into three sections that provide actionable guidelines for immediate application. The first section, Foundations for Data Agility, addresses friction between data and agile practitioners by classifying pattern levels of granularity and exposing their interdependencies. It establishes a context for various model types (conceptual, logical, physical, industry, enterprise, project) and teaches how to customize patterns within these frameworks. The second section, Steps Towards Data Agility, offers guidelines on generalizing and specializing patterns while cautioning against overreach. It encourages creativity in using patterns beyond their intended purposes, comparing the short-term "You Ain't Gonna Need It" (YAGNI) philosophy of agile practitioners with the strategic perspectives of architects. Topics include iterative modeling, creation of patterns, and the modeler's role in agile projects, culminating in a case study. The final section, A Bridge to the Land of Object Orientation, guides traditional data modelers in expanding their skills to engage with object-oriented de

You want the rigor of good data architecture at the speed of agile? Then this is the missing link - your step-by-step guide to Data Vault success. Success with a Data Vault starts with the business and ends with the business. Sure, there's some technical stuff in the middle, and it is absolutely essential - but it's not sufficient on its own. This book will help you shape the business perspective, and weave it into the more technical aspects of Data Vault modeling. You can read the foundational books and go on courses, but one massive risk still remains. Dan Linstedt, the founder of the Data Vault, very clearly directs those building a Data Vault to base its design on an "enterprise ontology". And Hans Hultgren similarly stresses the importance of the business concepts model. So it's important. We get that. But: What on earth is an enterprise ontology/business concept model, 'cause I won't know if I've got one if I don't know what I'm looking for? If I can't find one, how do I get my hands on such a thing? Even if I have one of these wonderful things, how do I apply it to get the sort of Data Vault that's recommended? It's actually not as hard as some would fear to answer all of these questions, and it's certainly worth the effort. This book just might save you a world of pain. It's a supplement to other material on Data Vault modeling, but it's the vital missing link to finding simplicity for Data Vault success.