Building a Scalable Data Warehouse with Data Vault 2 0

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. 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 warehouse Demystifies data vault modeling with beginning, intermediate, and advanced techniques Discusses the advantages of the data vault approach over other techniques, also including the latest updates to Data Vault 2.0 and multiple improvements to Data Vault 1.0

Produk Detail:

  • Author : Dan Linstedt
  • Publisher : Morgan Kaufmann
  • Pages : 684 pages
  • ISBN : 0128026480
  • Rating : 4/5 from 1 reviews
CLICK HERE TO GET THIS BOOKBuilding a Scalable Data Warehouse with Data Vault 2 0

Building a Scalable Data Warehouse with Data Vault 2.0

Building a Scalable Data Warehouse with Data Vault 2.0
  • Author : Dan Linstedt,Michael Olschimke
  • Publisher : Morgan Kaufmann
  • Release : 15 September 2015
GET THIS BOOKBuilding a Scalable Data Warehouse with Data Vault 2.0

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

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  • Publisher : Unknown Publisher
  • Release : 22 November 2015
GET THIS BOOKAn Introduction to Agile Data Engineering Using Data Vault 2. 0

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  • Publisher : CreateSpace
  • Release : 01 November 2011
GET THIS BOOKSuper Charge Your Data Warehouse

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  • Publisher : DecisionOne Consulting
  • Release : 01 November 2011
GET THIS BOOKAgile Data Warehouse Design

Agile Data Warehouse Design is a step-by-step guide for capturing data warehousing/business intelligence (DW/BI) requirements and turning them into high performance dimensional models in the most direct way: by modelstorming (data modeling ] brainstorming) with BI stakeholders. This book describes BEAM, an agile approach to dimensional modeling, for improving communication between data warehouse designers, BI stakeholders and the whole DW/BI development team. BEAM provides tools and techniques that will encourage DW/BI designers and developers to move away

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  • Publisher : Unknown Publisher
  • Release : 16 November 2012
GET THIS BOOKModeling the Agile Data Warehouse with Data Vault

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  • Publisher : Morgan Kaufmann
  • Release : 26 November 2014
GET THIS BOOKData Architecture: A Primer for the Data Scientist

Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the existing systems (data warehousing systems). Taking a look at the larger picture into which Big Data fits gives the data scientist the necessary context for how pieces of the puzzle should fit together. Most references

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  • Publisher : Academic Press
  • Release : 30 April 2019
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Over the past 5 years, the concept of big data has matured, data science has grown exponentially, and data architecture has become a standard part of organizational decision-making. Throughout all this change, the basic principles that shape the architecture of data have remained the same. There remains a need for people to take a look at the "bigger picture" and to understand where their data fit into the grand scheme of things. Data Architecture: A Primer for the Data Scientist, Second

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  • Release : 21 February 2019
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  • Publisher : Unknown Publisher
  • Release : 15 April 2019
GET THIS BOOKThe Elephant in the Fridge

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  • Release : 28 July 2010
GET THIS BOOKDW 2.0: The Architecture for the Next Generation of Data Warehousing

DW 2.0: The Architecture for the Next Generation of Data Warehousing is the first book on the new generation of data warehouse architecture, DW 2.0, by the father of the data warehouse. The book describes the future of data warehousing that is technologically possible today, at both an architectural level and technology level. The perspective of the book is from the top down: looking at the overall architecture and then delving into the issues underlying the components. This allows people who are

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  • Release : 08 March 2011
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  • Publisher : John Wiley & Sons
  • Release : 01 February 2016
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