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Building A Scalable Data Warehouse With Data Vault 2 0


Author : Dan Linstedt
language : en
Publisher: Morgan Kaufmann Publishers
Release Date : 2015-10-01

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" 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. Learn from the inventor of the Data Vault Methodology, Dan LinstedtProvides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast Explains the theoretical concepts and provides hands-on instruction on how to build and implement a data warehouseDemystifies Data Vault Modeling with beginning, intermediate, and advanced techniquesDiscusses 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

Navigating The Labyrinth


Author : Laura Sebastian-Coleman
language : en
Publisher: Technics Publications
Release Date : 2018-05-09

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An Executive Guide to Data Management

Data Architecture


Author : Charles Tupper
language : en
Publisher: Elsevier
Release Date : 2011-05-09

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Download Data Architecture written by Charles Tupper and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-09 with Computers categories.


Data Architecture: From Zen to Reality explains the principles underlying data architecture, how data evolves with organizations, and the challenges organizations face in structuring and managing their data. Using a holistic approach to the field of data architecture, the book describes proven methods and technologies to solve the complex issues dealing with data. It covers the various applied areas of data, including data modelling and data model management, data quality, data governance, enterprise information management, database design, data warehousing, and warehouse design. This text is a core resource for anyone customizing or aligning data management systems, taking the Zen-like idea of data architecture to an attainable reality. The book presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios. It teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions. It includes the detail needed to illustrate how the fundamental principles are used in current business practice. The book is divided into five sections, one of which addresses the software-application development process, defining tools, techniques, and methods that ensure repeatable results. Data Architecture is intended for people in business management involved with corporate data issues and information technology decisions, ranging from data architects to IT consultants, IT auditors, and data administrators. It is also an ideal reference tool for those in a higher-level education process involved in data or information technology management. Presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios Teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions Includes the detail needed to illustrate how the fundamental principles are used in current business practice

Getting Started With Talend Open Studio For Data Integration


Author : Jonathan Bowen
language : en
Publisher: Packt Publishing Ltd
Release Date : 2012-11-06

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Download Getting Started With Talend Open Studio For Data Integration written by Jonathan Bowen and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-06 with Computers categories.


A practical cookbook on building portals with GateIn including user security, gadgets, and every type of portlet possible.

Modeling The Agile Data Warehouse With Data Vault


Author : Hans Hultgren
language : en
Publisher:
Release Date : 2012-11-16

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Download Modeling The Agile Data Warehouse With Data Vault written by Hans Hultgren and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-16 with Data warehousing categories.


Data Modeling for Agile Data Warehouse using Data Vault Modeling Approach. Includes Enterprise Data Warehouse Architecture. This is a complete guide to the data vault data modeling approach. The book also includes business and program considerations for the agile data warehousing and business intelligence program. There are over 200 diagrams and figures concerning modeling, core business concepts, architecture, business alignment, semantics, and modeling comparisons with 3NF and Dimensional modeling.

Practical Data Science


Author : Andreas François Vermeulen
language : en
Publisher: Apress
Release Date : 2018-02-21

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Learn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets. The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions. What You'll Learn Become fluent in the essential concepts and terminology of data science and data engineering Build and use a technology stack that meets industry criteria Master the methods for retrieving actionable business knowledge Coordinate the handling of polyglot data types in a data lake for repeatable results Who This Book Is For Data scientists and data engineers who are required to convert data from a data lake into actionable knowledge for their business, and students who aspire to be data scientists and data engineers

Data Lake Architecture


Author : Bill Inmon
language : en
Publisher: Technics Publications
Release Date : 2016-04-01

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Download Data Lake Architecture written by Bill Inmon and has been published by Technics Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-01 with Computers categories.


Organizations invest incredible amounts of time and money obtaining and then storing big data in data stores called data lakes. But how many of these organizations can actually get the data back out in a useable form? Very few can turn the data lake into an information gold mine. Most wind up with garbage dumps. Data Lake Architecture will explain how to build a useful data lake, where data scientists and data analysts can solve business challenges and identify new business opportunities. Learn how to structure data lakes as well as analog, application, and text-based data ponds to provide maximum business value. Understand the role of the raw data pond and when to use an archival data pond. Leverage the four key ingredients for data lake success: metadata, integration mapping, context, and metaprocess. Bill Inmon opened our eyes to the architecture and benefits of a data warehouse, and now he takes us to the next level of data lake architecture.