Provides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast.Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture.Important data warehouse technologies and practices.How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes.Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: 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. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. ' 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. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. 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. The Data Vault was invented by Dan Linstedt at the U.S. Relevant topics of discussion include Big Data, NoSQL, cloud technologies, and cybersecurity considerations pertinent to such systems.Название: Building a Scalable Data Warehouse with Data Vault 2.0 It covers the foundational concepts and techniques of data storage and retrieval, with an emphasis on distributed or cloud-based architectures. This course explores the key technical and design considerations underpinning the data architectures that support modern data-intensive systems. Unfortunately, I can't link to the syllabus, but here's the course synopsis: Eventually, I intend to make it more of a cloud-based project but at this time it's really just designed to walk students through some of the key phases in the data engineering pipeline.Īt the moment, those two are the primary course texts, and they are supplemented with some extra articles or videos. The assignments are mostly reading-based, with a hands-on group project throughout the quarter to develop a toy data pipeline project. It's a new course and still needs some polishing.

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