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An Introduction to Agile Data Engineering Using Data Vault 2.0: Better Data Modeling
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JMD 3935
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The Data Vault System of Business Intelligence provides a method and approach to modeling your enterprise data warehouse (EDW) that is agile, flexible, and scalable.
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- The world of data warehousing is changing. Big Data & Agile are hot topics. But companies still need to collect, report, and analyze their data. Usually this requires some form of data warehousing or business intelligence system. So how do we do that in the modern IT landscape in a way that allows us to be agile and either deal directly or indirectly with unstructured and semi structured data?The Data Vault System of Business Intelligence provides a method and approach to modeling your enterprise data warehouse (EDW) that is agile, flexible, and scalable. This book will give you a short introduction to Agile Data Engineering for Data Warehousing and Data Vault 2.0. I will explain why you should be trying to become Agile, some of the history and rationale for Data Vault 2.0, and then show you the basics for how to build a data warehouse model using the Data Vault 2.0 standards.In addition, I will cover some details about the Business Data Vault (what it is) and then how to build a virtual Information Mart off your Data Vault and Business Vault using the Data Vault 2.0 architecture.So if you want to start learning about Agile Data Engineering with Data Vault 2.0, this book is for you.
| Publisher | Independently published |
| Publication date | November 22, 2015 |
| Language | English |
| Print length | 50 pages |
| ISBN-10 | 1796584932 |
| ISBN-13 | 978-1796584936 |
| Item Weight | 6.7 ounces (189.95 grams) |
| Dimensions | 8.5 x 0.12 x 11 inches (21.6 x 0.3 x 27.9 cm) |
Who Should Buy?
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Data Professionals
Data engineers and analysts seeking to enhance their skills in agile data modeling using Data Vault 2.0.
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Agile Teams
Teams adopting Agile methodologies looking for efficient data engineering practices to improve collaboration and delivery speed.
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Businesses Transitioning
Organizations transitioning to data-driven strategies that need robust and scalable data modeling frameworks for improved insights.
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Beginners
Individuals with no prior understanding of data engineering or modeling may find the content too advanced or technical.
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Data Modeling & Design Editorial Review
**** The reception of this book on Data Vault modeling has been largely mixed, with numerous customers expressing disappointment regarding its presentation and depth. Despite its recognition in the field, many readers found it to be lacking substance, describing it as more of a pamphlet than a comprehensive guide. While the book promises an overview of Data Vault concepts, those familiar with the subject matter felt it merely rehashes existing knowledge without offering significant new insights. The layout was criticized heavily, particularly the small size of the ER diagrams, making it difficult to glean valuable information even with magnification. The absence of page numbers added to the frustration, compounding issues linked to its self-published nature and overall editing quality. On the positive side, some reviews acknowledged that the content, albeit compact and straightforward, is valuable for newcomers to the Data Vault methodology. While it touches on various data vault structures, seasoned readers recommend supplementing this book with more comprehensive texts like Lindsted's DV2 for a deeper understanding. There is also a perception that the primary insights available could likely be gleaned from Kent's blog, suggesting that the book may not be the most effective medium for learning. For readers specifically seeking an introductory or simplified view of Data Vault modeling, this book might serve as a useful starting point. However, those with prior exposure to the concepts may find it largely unfulfilling and poorly formatted. **
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Pros
- Compact and to-the-point overview useful for beginners.
- Solid foundational knowledge, albeit not extensive.
- Could serve as a catalyst for further exploration of the subject through other resources.
Cons
- Poor layout and formatting, especially with ER diagrams being unreadable.
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JMD 3935
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Features & Benefits
- Learn how Agile Data Engineering can revolutionize data warehousing
- Understand the rationale and history behind Data Vault 2.0
- Discover the basics of building a data warehouse model using Data Vault 2.0 standards
- Explore Business Data Vault and building a virtual Information Mart
- Ideal for those looking to start learning about Agile Data Engineering with Data Vault 2.0
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