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Building A Scalable Data Warehouse With Data Vault 2 0

Author : Dan Linstedt
ISBN : 9780128026489
Genre : Computers
File Size : 58. 22 MB
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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

Building A Scalable Data Warehouse With Data Vault 2 0 Implementation Guide For Microsoft Sql Server 2014

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ISBN : OCLC:972041598
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File Size : 83. 39 MB
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Super Charge Your Data Warehouse

Author : Dan Linstedt
ISBN : 1463778686
Genre : Computers
File Size : 68. 8 MB
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Do You Know If Your Data Warehouse Flexible, Scalable, Secure and Will It Stand The Test Of Time And Avoid Being Part Of The Dreaded "Life Cycle"? The Data Vault took the Data Warehouse world by storm when it was released in 2001. Some of the world's largest and most complex data warehouse situations understood the value it gave especially with the capabilities of unlimited scaling, flexibility and security. Here is what industry leaders say about the Data Vault "The Data Vault is the optimal choice for modeling the EDW in the DW 2.0 framework" - Bill Inmon, The Father of Data Warehousing "The Data Vault is foundationally strong and an exceptionally scalable architecture" - Stephen Brobst, CTO, Teradata "The Data Vault should be considered as a potential standard for RDBMS-based analytic data management by organizations looking to achieve a high degree of flexibility, performance and openness" - Doug Laney, Deloitte Analytics Institute "I applaud Dan's contribution to the body of Business Intelligence and Data Warehousing knowledge and recommend this book be read by both data professionals and end users" - Howard Dresner, From the Foreword - Speaker, Author, Leading Research Analyst and Advisor You have in your hands the work, experience and testing of 2 decades of building data warehouses. The Data Vault model and methodology has proven itself in hundreds (perhaps thousands) of solutions in Insurance, Crime-Fighting, Defense, Retail, Finance, Banking, Power, Energy, Education, High-Tech and many more. Learn the techniques and implement them and learn how to build your Data Warehouse faster than you have ever done before while designing it to grow and scale no matter what you throw at it. Ready to "Super Charge Your Data Warehouse"?

Information Modelling And Knowledge Bases Xxviii

Author : H. Jaakkola
ISBN : 9781614997207
Genre : Computers
File Size : 61. 80 MB
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Information modelling and knowledge bases are now essential, not only to academics working in computer science, but also wherever information technology is applied. This book presents papers from the 26th International Conference on Information Modelling and Knowledge Bases (formerly the European Japanese Conference – EJC), which took place in Tampere, Finland, in June 2016. The conference provides a platform to bring together researchers and practitioners working with information modelling and knowledge bases, and the 33 accepted papers cover topics including: conceptual modelling; knowledge and information modelling and discovery; linguistic modelling; cross-cultural communication and social computing; environmental modelling and engineering; and multimedia data modelling and systems. All papers were improved and resubmitted for publication after the conference. Covering state-of-the-art research and practice, the book will be of interest to all those whose work involves information modelling and knowledge bases.

Achieving Buzzword Compliance

Author : David C. Hay
ISBN : 9781634623728
Genre : Computers
File Size : 90. 90 MB
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Understand the language and vocabulary of Data Architecture. The Data Architecture field is rife with terms that have become “fashionable”. Some of the terms began with very specific, specialized, meanings – but as their use spread, they lost the precision of their technical definitions and become, well, “buzzwords”. A buzzword is “a word or expression from a particular subject area that has become fashionable because it has been used a lot”. Compliance is “the obeying of an accepted principle or instruction that states the way things are or should be done.” The assignment is to take buzzwords and follow rules to use them correctly. We cut through the hype to arrive at buzzword compliance – the state where you fully understand the words that in fact have real meaning in the data architecture industry. This book will rationalize the various ways all these terms are defined. Of necessity, the book must address all aspects of describing an enterprise and its data management technologies. This includes a wide range of subjects, from entity/relationship modeling, through the semantic web, to database issues like relational and “beyond relational” (“NoSQL”) approaches. In each case, the definitions for the subject are meant to be detailed enough to make it possible to understand basic principles—while recognizing that a full understanding will require consulting the sources where they are more completely described. The book’s Glossary contains a catalogue of definitions and its Bibliography contains a comprehensive set of references.

Advances In Conceptual Modeling

Author : Sergio de Cesare
ISBN : 9783319706252
Genre : Computers
File Size : 40. 25 MB
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This book constitutes the refereed proceedings of five workshops and a symposium, held at the 36th International Conference on Conceptual Modeling, ER 2017, in Valencia, Spain in November 2017. The 21 revised full papers were carefully reviewed and selected out of 47 submissions to the following events: AHA 2017 - 3rd International Workshop on Modeling for Ambient Assistance and Healthy Ageing MoBiD 2017 - 6th International Workshop on Modeling and Management of Big Data MREBA 2017 - 4th International Workshop on Conceptual Modeling in Requirements and Business Analysis OntoCom 2017 - 5th International Workshop on Ontologies and Conceptual Modeling QMMQ 2017 - 4th Workshop on Quality of Models and Models of Quality

Data Architecture A Primer For The Data Scientist

Author : W.H. Inmon
ISBN : 9780128020913
Genre : Computers
File Size : 33. 94 MB
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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 on Big Data look at only one tiny part of a much larger whole. Until data gathered can be put into an existing framework or architecture it can’t be used to its full potential. Data Architecture a Primer for the Data Scientist addresses the larger architectural picture of how Big Data fits with the existing information infrastructure, an essential topic for the data scientist. Drawing upon years of practical experience and using numerous examples and an easy to understand framework. W.H. Inmon, and Daniel Linstedt define the importance of data architecture and how it can be used effectively to harness big data within existing systems. You’ll be able to: Turn textual information into a form that can be analyzed by standard tools. Make the connection between analytics and Big Data Understand how Big Data fits within an existing systems environment Conduct analytics on repetitive and non-repetitive data Discusses the value in Big Data that is often overlooked, non-repetitive data, and why there is significant business value in using it Shows how to turn textual information into a form that can be analyzed by standard tools. Explains how Big Data fits within an existing systems environment Presents new opportunities that are afforded by the advent of Big Data Demystifies the murky waters of repetitive and non-repetitive data in Big Data

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