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- Autorius: Dan Linstedt, Michael Olschimke
- Leidėjas: Elsevier LTD, Oxford
- Metai: 2015
- ISBN-10: 0128025107
- ISBN-13: 9780128025109
- Formatas: 18.4 x 23.1 x 4 cm, minkšti viršeliai
- Kalba: Anglų
- Extra -20 % nuolaida šiai knygai su kodu ENG20
Building a Scalable Data Warehouse with Data Vault 2.0 + nemokamas atvežimas! | knygos.lt
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Building a Scalable Data Warehouse with Data Vault 2.0 covers everything users need to create a scalable data warehouse from scratch, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. In addition, the book presents tactics on how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 standard. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Listedt and Michael Olschimke discuss tactics on how to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes, important data warehouse technologies and practices, and data quality services (DQS) and master data services (MDS) in the context of the data vault architecture.
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- Autorius: Dan Linstedt, Michael Olschimke
- Leidėjas: Elsevier LTD, Oxford
- Metai: 2015
- ISBN-10: 0128025107
- ISBN-13: 9780128025109
- Formatas: 18.4 x 23.1 x 4 cm, minkšti viršeliai
- Kalba: Anglų
Building a Scalable Data Warehouse with Data Vault 2.0 covers everything users need to create a scalable data warehouse from scratch, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. In addition, the book presents tactics on how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 standard. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Listedt and Michael Olschimke discuss tactics on how to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes, important data warehouse technologies and practices, and data quality services (DQS) and master data services (MDS) in the context of the data vault architecture.
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