Building Scalable Data Warehouse by Linstedt Daniel (28 results)

paperback. Condition: Good.

Paperback. Condition: Fair. 1. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

Paperback. Condition: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Condition: Very Good. SIGNED BY DANIEL LINSTEDT A copy that has been read, but remains in excellent condition. Pages are intact and are not marred by notes or highlighting. The spine remains undamaged. There are no stickers on book or rips in dust cover.

Softcover. Condition: Fine. Leichte Rillen / Abschürfungen / Risse / Knicke; Gebrochener Buchrücken. The Data Vault, created by Dan Linstedt at the U.S. Department of Defense, has been effectively implemented in data warehousing projects across various organizations. Its nature-inspired, simplified design helps mitigate common data warehousing failures. This resource provides comprehensive guidance on building a scalable data warehouse from start to finish, focusing on the Data Vault modeling technique that underpins a technical data warehouse layer. It emphasizes an incremental approach using the agile Data Vault 2.0 methodology. Readers will learn to construct both the input layer (stage layer) and the presentation layer (data mart) within the Data Vault 2.0 architecture, along with best practices for implementation. Drawing from extensive practical experience, the authors present numerous examples within an accessible framework. Key topics include loading each layer using SQL Server Integration Services (SSIS) and automating Data Vault loading processes. The book also covers essential data warehouse technologies, Data Quality Services (DQS), and Master Data Services (MDS) in relation to the Data Vault architecture. It offers a thorough introduction to data warehousing, blending theoretical concepts with hands-on instruction, while demystifying data vault modeling through various techniques. Additionally, it highlights the advantages of the data vault approach over other methods, including updates and enhancements to Data V.

Paperback. Condition: New. The Data Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. "Building a Scalable Data Warehouse" covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: 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. Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Softcover. Condition: Fine. Autorensignatur; Gebrochener Buchrücken. The Data Vault, created by Dan Linstedt at the U.S. Department of Defense, has been effectively implemented in data warehousing projects across various organizations. Its nature-inspired, simplified design helps mitigate common data warehousing failures. This resource provides comprehensive guidance on building a scalable data warehouse from start to finish, focusing on the Data Vault modeling technique that underpins a technical data warehouse layer. It emphasizes an incremental approach using the agile Data Vault 2.0 methodology. Readers will learn to construct both the input layer (stage layer) and the presentation layer (data mart) within the Data Vault 2.0 architecture, along with best practices for implementation. Drawing from extensive practical experience, the authors present numerous examples within an accessible framework. Key topics include loading each layer using SQL Server Integration Services (SSIS) and automating Data Vault loading processes. The book also covers essential data warehouse technologies, Data Quality Services (DQS), and Master Data Services (MDS) in relation to the Data Vault architecture. It offers a thorough introduction to data warehousing, blending theoretical concepts with hands-on instruction, while demystifying data vault modeling through various techniques. Additionally, it highlights the advantages of the data vault approach over other methods, including updates and enhancements to Data V.

Condition: New. pp. 640.

Condition: New. In.

Condition: Nuevo. Encuadernación: Tapa blanda o bolsillo | Páginas: 661 | Dimensiones: 200 x 300 - Tecnología.

Bolsillo. Condition: New. Dust Jacket Condition: Nuevo. 01. LIBRO.

Paperback. Condition: new. New Copy. Customer Service Guaranteed.

Condition: Nuevo. Building a scalable data warehouse with data vault 2.0 editado por Elsevier uk.

Taschenbuch. Condition: Neu. Neuware -The Data Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. 'Building a Scalable Data Warehouse' covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: 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. Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture. 661 pp. Englisch.

Taschenbuch. Condition: Neu. Neuware -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.

Condition: New. pp. 640.

Condition: New. pp. 640.

Condition: New. Provides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast Explains theoretical concepts and provides hands-on instruction on how to build and implement a data wareh.

Taschenbuch. Condition: Neu. Neuware -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.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 661 pp. Englisch.

Paperback. Condition: New. The Data Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. "Building a Scalable Data Warehouse" covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: 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. Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture.

Taschenbuch. Condition: Neu. Building a Scalable Data Warehouse with Data Vault 2.0 | Daniel Linstedt (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2015 | Elsevier LTD | EAN 9780128025109 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Bolsillo. Condition: New. Dust Jacket Condition: Nuevo. 01. LIBRO.

Taschenbuch. Condition: Neu. Neuware -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. 661 pp. Englisch.

Condition: new. Questo è un articolo print on demand.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The Data Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. 'Building a Scalable Data Warehouse' covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: 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. Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture. 661 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The Data Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. 'Building a Scalable Data Warehouse' covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: 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. Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture.