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The Data Vault Guru

a pragmatic guide on building a data vault

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  • 676 stránek
  • 24 hodin čtení

Více o knize

The data vault methodology presents a unique opportunity to model the enterprise data warehouse using the same automation principles applicable in today’s software delivery, continuous integration, continuous delivery and continuous deployment while still maintaining the standards expected for governing a corporation’s most valuable asset: data. This book provides at first the landscape of a modern architecture and then as a thorough guide on how to deliver a data model that flexes as the enterprise flexes, the data vault. Whether the data is structured, semi-structured or even unstructured one thing is clear, there is always a model either applied early (schema-on-write) or applied late (schema-on-read). Today’s focus on data governance requires that we know what we retain about our customers, the data vault provides that focus by delivering a methodology focused on all aspects about the customer and provides some of the best practices for modern day data compliance. The book will delve into every data vault modelling artefact, its automation with sample code, raw vault, business vault, testing framework, a build framework, sample data vault models, how to build automation patterns on top of a data vault and even offer an extension of data vault that provides automated timeline correction, not to mention variation of data vault designed to provide audit trails, metadata control and integration with agile delivery tools.

Nákup knihy

The Data Vault Guru, Patrick Cuba

Jazyk
Rok vydání
2020
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Titul
The Data Vault Guru
Podtitul
a pragmatic guide on building a data vault
Jazyk
anglicky
Rok vydání
2020
Vazba
měkká
Počet stran
676
ISBN13
9798691308086
Série
Štítky
Anotace
The data vault methodology presents a unique opportunity to model the enterprise data warehouse using the same automation principles applicable in today’s software delivery, continuous integration, continuous delivery and continuous deployment while still maintaining the standards expected for governing a corporation’s most valuable asset: data. This book provides at first the landscape of a modern architecture and then as a thorough guide on how to deliver a data model that flexes as the enterprise flexes, the data vault. Whether the data is structured, semi-structured or even unstructured one thing is clear, there is always a model either applied early (schema-on-write) or applied late (schema-on-read). Today’s focus on data governance requires that we know what we retain about our customers, the data vault provides that focus by delivering a methodology focused on all aspects about the customer and provides some of the best practices for modern day data compliance. The book will delve into every data vault modelling artefact, its automation with sample code, raw vault, business vault, testing framework, a build framework, sample data vault models, how to build automation patterns on top of a data vault and even offer an extension of data vault that provides automated timeline correction, not to mention variation of data vault designed to provide audit trails, metadata control and integration with agile delivery tools.