The Business Of Data Vault Modeling

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The Business Of Data Vault Modeling

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Author : Daniel Lindstedt
language : en
Publisher: Lulu.com
Release Date : 2009

The Business Of Data Vault Modeling written by Daniel Lindstedt and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.

Building A Scalable Data Warehouse With Data Vault 2 0

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Author : Daniel Linstedt
language : en
Publisher: Morgan Kaufmann
Release Date : 2015-09-15

Building A Scalable Data Warehouse With Data Vault 2 0 written by Daniel Linstedt and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-15 with Computers categories.

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

Data Architecture A Primer For The Data Scientist

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Author : W.H. Inmon
language : en
Publisher: Morgan Kaufmann
Release Date : 2014-11-26

Data Architecture A Primer For The Data Scientist written by W.H. Inmon and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-26 with Computers categories.

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

Information Modelling And Knowledge Bases Xxviii

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Author : H. Jaakkola
language : en
Publisher: IOS Press
Release Date : 2017-01-03

Information Modelling And Knowledge Bases Xxviii written by H. Jaakkola and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-03 with Computers categories.

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.

Artificial Intelligence With Microsoft Power Bi

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Author : Jen Stirrup
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-03-28

Artificial Intelligence With Microsoft Power Bi written by Jen Stirrup and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-28 with Computers categories.

Advance your Power BI skills by adding AI to your repertoire at a practice level. With this practical book, business-oriented software engineers and developers will learn the terminologies, practices, and strategy necessary to successfully incorporate AI into your business intelligence estate. Jen Stirrup, CEO of AI and BI leadership consultancy Data Relish, and Thomas Weinandy, research economist at Upside, show you how to use data already available to your organization. Springboarding from the skills that you already possess, this book adds AI to your organization's technical capability and expertise with Microsoft Power BI. By using your conceptual knowledge of BI, you'll learn how to choose the right model for your AI work and identify its value and validity. Use Power BI to build a good data model for AI Demystify the AI terminology that you need to know Identify AI project roles, responsibilities, and teams for AI Use AI models, including supervised machine learning techniques Develop and train models in Azure ML for consumption in Power BI Improve your business AI maturity level with Power BI Use the AI feedback loop to help you get started with the next project

Database Modeling Step By Step

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Author : Gavin Powell
language : en
Publisher: CRC Press
Release Date : 2020-01-06

Database Modeling Step By Step written by Gavin Powell and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-06 with Computers categories.

With the aim of simplifying relational database modeling, Database Modeling Step-by-Step presents the standard approach to database normalization and then adds its own approach, which is a more simplistic, intuitive way to building relational database models. Going from basics to contemporary topics, the book opens with relational data modeling and ends with BigData database modeling following a road map of the evolution in relational modeling and including brief introductions to data warehousing and BigData modeling. A break-down of the elements of a model explains what makes up a relational data model. This is followed by a comparison between standard normalization and a more simplistic intuitive approach to data modeling that a beginner can follow and understand. A brief chapter explains how to use the database programming language SQL (Structured Query Language), which reads from and writes to a relational database. SQL is fundamental to data modeling because it helps in understanding how the model is used. In addition to the relational model, the last three chapters cover important modern world topics including denormalization that leads into data warehouses and BigData database modeling. The book explains how there is not much to logical data modeling in BigData databases because as they are often schema-less, which means that BigData databases do not have schemas embedded into the database itself, they have no metadata and thus not much of a logical data model. Online bonus chapters include a case study that covers relational data modeling and are available at the author’s web site: www.oracletroubleshooter.com/datamodeling.html

Data Modeling With Snowflake

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Author : Serge Gershkovich
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-05-31

Data Modeling With Snowflake written by Serge Gershkovich 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 2023-05-31 with Computers categories.

Discover how Snowflake's unique objects and features can be used to leverage universal modeling techniques through real-world examples and SQL recipes Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn core modeling techniques tied to practical examples using native Snowflake architecture Adopt a universal modeling language to communicate business value to functional teams Go beyond physical modeling with SQL recipes to transform and shape your Snowflake data Book DescriptionThe Snowflake Data Cloud is one of the fastest-growing platforms for data warehousing and application workloads. Snowflake's scalable, cloud-native architecture and expansive set of features and objects enables you to deliver data solutions quicker than ever before. Yet, we must ensure that these solutions are developed using recommended design patterns and accompanied by documentation that’s easily accessible to everyone in the organization. This book will help you get familiar with simple and practical data modeling frameworks that accelerate agile design and evolve with the project from concept to code. These universal principles have helped guide database design for decades, and this book pairs them with unique Snowflake-native objects and examples like never before – giving you a two-for-one crash course in theory as well as direct application. By the end of this Snowflake book, you’ll have learned how to leverage Snowflake’s innovative features, such as time travel, zero-copy cloning, and change-data-capture, to create cost-effective, efficient designs through time-tested modeling principles that are easily digestible when coupled with real-world examples.What you will learn Discover the time-saving benefits and applications of data modeling Learn about Snowflake's cloud-native architecture and its features Understand and apply modeling techniques using Snowflake objects Universal modeling concepts and language through Snowflake objects Get comfortable reading and transforming semistructured data Learn directly with pre-built recipes and examples Learn to apply modeling frameworks from Star to Data Vault Who this book is for This book is for developers working with SQL who are looking to build a strong foundation in modeling best practices and gain an understanding of where they can be effectively applied to save time and effort. Whether you’re an ace in SQL logic or starting out in database design, this book will equip you with the practical foundations of data modeling to guide you on your data journey with Snowflake. Developers who’ve recently discovered Snowflake will be able to uncover its core features and learn to incorporate them into universal modeling frameworks.

Fundamentals Of Data Engineering

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Author : Joe Reis
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-06-22

Fundamentals Of Data Engineering written by Joe Reis and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-22 with Computers categories.

"Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you will learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available in the framework of the data engineering lifecycle. Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to stitch together a variety of cloud technologies to serve the needs of downstream data consumers. You will understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, governance, and deployment that are critical in any data environment regardless of the underlying technology. This book will help you: Assess data engineering problems using an end-to-end data framework of best practices Cut through marketing hype when choosing data technologies, architecture, and processes Use the data engineering lifecycle to design and build a robust architecture Incorporate data governance and security across the data engineering lifecycle." - from Publisher.

Advanced Research In Technologies Information Innovation And Sustainability

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Author : Teresa Guarda
language : en
Publisher: Springer Nature
Release Date : 2025-03-12

Advanced Research In Technologies Information Innovation And Sustainability written by Teresa Guarda and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-12 with Computers categories.

This three-volume set, CCIS 2345-2347, constitutes the revised selected papers from the 4th International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability 2024, ARTIIS 2024, held in Santiago de Chile, Chile, during October 21-23, 2024. The 83 full papers and 8 short papers included in these proceedings were carefully reviewed and selected from 238 submissions. These papers are categorized under the following topical sections:- Part I: Computing Solutions Part II: Data Intelligence Part III: Sustainability; Ethics, Security, and Privacy

Proceedings Of 23rd International Conference On Informatics In Economy Ie 2024

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Author : Cristian Ciurea
language : en
Publisher: Springer Nature
Release Date : 2025-04-12

Proceedings Of 23rd International Conference On Informatics In Economy Ie 2024 written by Cristian Ciurea and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-12 with Computers categories.

This book includes high-quality research papers presented at 23rd International Conference on Informatics in Economy (IE 2024), which is held in Bucharest, Romania, during May 2024. This book covers research results in business informatics and related computer science topics, such as IoT, mobile-embedded and multimedia solutions, e-society, enterprise and business solutions, databases and big data, artificial intelligence, data mining and machine learning, quantitative economics.