Download or read book Building a Scalable Data Warehouse with Data Vault 2 0 written by Daniel Linstedt and published by Morgan Kaufmann. This book was released on 2015-09-15 with total page 684 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Data Vault Standard Requirements written by Gerardus Blokdyk and published by . This book was released on 2018-05-12 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: Where do ideas that reach policy makers and planners as proposals for Data vault strengthening and reform actually originate? To what extent does management recognize Data vault as a tool to increase the results? How can you negotiate Data vault successfully with a stubborn boss, an irate client, or a deceitful coworker? Who will be responsible for deciding whether Data vault goes ahead or not after the initial investigations? Does Data vault systematically track and analyze outcomes for accountability and quality improvement? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Data vault investments work better. This Data vault All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Data vault Self-Assessment. Featuring new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Data vault improvements can be made. In using the questions you will be better able to: - diagnose Data vault projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Data vault and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Data vault Scorecard, you will develop a clear picture of which Data vault areas need attention. Your purchase includes access details to the Data vault self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. Your exclusive instant access details can be found in your book.

Download or read book The Business of Data Vault Modeling written by Daniel Lindstedt and published by Lulu.com. This book was released on 2009 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Data Vault Guru written by Patrick Cuba and published by . This book was released on 2020-10-06 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: The data vault methodology presents a unique opportunity to model the enterprise data warehouse using the same automation principles applicable in today's software delivery, continuous integration, continuous delivery and continuous deployment while still maintaining the standards expected for governing a corporation's most valuable asset: data. This book provides at first the landscape of a modern architecture and then as a thorough guide on how to deliver a data model that flexes as the enterprise flexes, the data vault. Whether the data is structured, semi-structured or even unstructured one thing is clear, there is always a model either applied early (schema-on-write) or applied late (schema-on-read). Today's focus on data governance requires that we know what we retain about our customers, the data vault provides that focus by delivering a methodology focused on all aspects about the customer and provides some of the best practices for modern day data compliance.The book will delve into every data vault modelling artefact, its automation with sample code, raw vault, business vault, testing framework, a build framework, sample data vault models, how to build automation patterns on top of a data vault and even offer an extension of data vault that provides automated timeline correction, not to mention variation of data vault designed to provide audit trails, metadata control and integration with agile delivery tools.

Download or read book An Introduction to Agile Data Engineering Using Data Vault 2 0 written by Kent Graziano and published by . This book was released on 2015-11-22 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Super Charge Your Data Warehouse written by Dan Linstedt and published by Createspace Independent Publishing Platform. This book was released on 2011-11-11 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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"?

Download or read book Modeling the Agile Data Warehouse with Data Vault written by Hans Hultgren and published by . This book was released on 2012-11-16 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Corporate Information Factory written by W. H. Inmon and published by John Wiley & Sons. This book was released on 2002-03-14 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: The "father of data warehousing" incorporates the latesttechnologies into his blueprint for integrated decision supportsystems Today's corporate IT and data warehouse managers are required tomake a small army of technologies work together to ensure fast andaccurate information for business managers. Bill Inmon created theCorporate Information Factory to solve the needs ofthese managers. Since the First Edition, the design of the factoryhas grown and changed dramatically. This Second Edition, revisedand expanded by 40% with five new chapters, incorporates thesechanges. This step-by-step guide will enable readers to connecttheir legacy systems with the data warehouse and deal with a hostof new and changing technologies, including Web access mechanisms,e-commerce systems, ERP (Enterprise Resource Planning) systems. Thebook also looks closely at exploration and data mining servers foranalyzing customer behavior and departmental data marts forfinance, sales, and marketing.

Download or read book Data Architecture A Primer for the Data Scientist written by W.H. Inmon and published by Academic Press. This book was released on 2019-04-30 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past 5 years, the concept of big data has matured, data science has grown exponentially, and data architecture has become a standard part of organizational decision-making. Throughout all this change, the basic principles that shape the architecture of data have remained the same. There remains a need for people to take a look at the "bigger picture" and to understand where their data fit into the grand scheme of things. Data Architecture: A Primer for the Data Scientist, Second Edition addresses the larger architectural picture of how big data fits within the existing information infrastructure or data warehousing systems. This is an essential topic not only for data scientists, analysts, and managers but also for researchers and engineers who increasingly need to deal with large and complex sets of data. Until data are gathered and can be placed into an existing framework or architecture, they cannot be used to their full potential. Drawing upon years of practical experience and using numerous examples and case studies from across various industries, the authors seek to explain this larger picture into which big data fits, giving data scientists the necessary context for how pieces of the puzzle should fit together. New case studies include expanded coverage of textual management and analytics New chapters on visualization and big data Discussion of new visualizations of the end-state architecture

Download or read book The Nimble Elephant written by John Giles and published by Technics Publications. This book was released on 2012-08-01 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Get it done well and get it done fast” are twin, apparently opposing, demands. Data architects are increasingly expected to deliver quality data models in challenging timeframes, and agile developers are increasingly expected to ensure that their solutions can be easily integrated with the data assets of the overall organization. If you need to deliver quality solutions despite exacting schedules, “The Nimble Elephant” will help by describing proven techniques that leverage the libraries of published data model patterns to rapidly assemble extensible and robust designs. The three sections in the book provide guidelines for applying the lessons to your own situation, so that you can apply the techniques and patterns immediately to your current assignments. The first section, Foundations for Data Agility, addresses some perceived aspects of friction between “data” and “agile” practitioners. As a starting point for resolving the differences, pattern levels of granularity are classified, and their interdependencies exposed. A context of various types of models is established (e.g. conceptual / logical / physical, and industry / enterprise / project), and you will learn how to customize patterns within specific model types. The second section, Steps Towards Data Agility, shares guidelines on generalizing and specializing, with cautions on the dangers of going too far. Creativity in using patterns beyond their intended purpose is encouraged. The short-term “You Ain’t Gonna Need It” (YAGNI) philosophy of agile practitioners, and the longer-term strategic perspectives of architects, are compared and evaluated. Consideration is given to the potential of enterprise views contributing to project-specific models. Other topics include industry models, iterative modeling, creation of patterns when none exist, and patterns for rules-in-data. The section ends with a perspective on the modeler’s possible role in agile projects, followed by a case study. The final section, A Bridge to the Land of Object Orientation, provides a pathway for re-skilling traditional data modelers who want to expand their options by actively engaging with the ranks of object-oriented developers. I’m delighted to see that John has put his extensive experience and broad knowledge of data modeling into print! John’s ability to simplify the complex, and to share his knowledge and enthusiasm – and humor – with colleagues, comes through in this very useful and readable book. I recommend it to anyone working with data. — Monika Remenyi, Senior Data Architect, Telstra John Giles has written a compelling and engaging book about the importance of data modeling patterns in the world of agile computing. His book is clearly and simply written, and it is full of excellent examples drawn from his extensive experience as a practitioner. You will see the enthusiasm and passion that John clearly has for his work in data modeling. And you will see in his book that any interchange with John will always have its fair share of good humor and wisdom! — Professor Ron Weber, Dean, Faculty of IT, Monash University

Download or read book Data Mapping for Data Warehouse Design written by Qamar Shahbaz and published by Elsevier. This book was released on 2015-12-08 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mapping in a data warehouse is the process of creating a link between two distinct data models’ (source and target) tables/attributes. Data mapping is required at many stages of DW life-cycle to help save processor overhead; every stage has its own unique requirements and challenges. Therefore, many data warehouse professionals want to learn data mapping in order to move from an ETL (extract, transform, and load data between databases) developer to a data modeler role. Data Mapping for Data Warehouse Design provides basic and advanced knowledge about business intelligence and data warehouse concepts including real life scenarios that apply the standard techniques to projects across various domains. After reading this book, readers will understand the importance of data mapping across the data warehouse life cycle. Covers all stages of data warehousing and the role of data mapping in each Includes a data mapping strategy and techniques that can be applied to many situations Based on the author’s years of real-world experience designing solutions

Download or read book Data Warehousing in the Age of Big Data written by Krish Krishnan and published by Newnes. This book was released on 2013-05-02 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing data warehouse. As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture options, workloads, and integration techniques for Big Data and the data warehouse. Part 3 deals with data governance, data visualization, information life-cycle management, data scientists, and implementing a Big Data–ready data warehouse. Extensive appendixes include case studies from vendor implementations and a special segment on how we can build a healthcare information factory. Ultimately, this book will help you navigate through the complex layers of Big Data and data warehousing while providing you information on how to effectively think about using all these technologies and the architectures to design the next-generation data warehouse. Learn how to leverage Big Data by effectively integrating it into your data warehouse. Includes real-world examples and use cases that clearly demonstrate Hadoop, NoSQL, HBASE, Hive, and other Big Data technologies Understand how to optimize and tune your current data warehouse infrastructure and integrate newer infrastructure matching data processing workloads and requirements

Download or read book IBM Cloud Object Storage System Product Guide written by Vasfi Gucer and published by IBM Redbooks. This book was released on 2023-06-14 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Object storage is the primary storage solution that is used in the cloud and on-premises solutions as a central storage platform for unstructured data. IBM Cloud Object Storage is a software-defined storage (SDS) platform that breaks down barriers for storing massive amounts of data by optimizing the placement of data on commodity x86 servers across the enterprise. This IBM Redbooks® publication describes the major features, use case scenarios, deployment options, configuration details, initial customization, performance, and scalability considerations of IBM Cloud Object Storage on-premises offering. For more information about the IBM Cloud Object Storage architecture and technology that is behind the product, see IBM Cloud Object Storage Concepts and Architecture , REDP-5537. The target audience for this publication is IBM Cloud Object Storage IT specialists and storage administrators.

Download or read book Adaptive Mobile Computing written by Mauro Migliardi and published by Academic Press. This book was released on 2017-08-01 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Mobile Computing: Advances in Processing Mobile Data Sets explores the latest advancements in producing, processing and securing mobile data sets. The book provides the elements needed to deepen understanding of this trend which, over the last decade, has seen exponential growth in the number and capabilities of mobile devices. The pervasiveness, sensing capabilities and computational power of mobile devices have turned them into a fundamental instrument in everyday life for a large part of the human population. This fact makes mobile devices an incredibly rich source of data about the dynamics of human behavior, a pervasive wireless sensors network with substantial computational power and an extremely appealing target for a new generation of threats. Offers a coherent and realistic image of today's architectures, techniques, protocols, components, orchestration, choreography and development related to mobile computing Explains state-of-the-art technological solutions for the main issues hindering the development of next-generation pervasive systems including: supporting components for collecting data intelligently, handling resource and data management, accounting for fault tolerance, security, monitoring and control, addressing the relation with the Internet of Things and Big Data and depicting applications for pervasive context-aware processing Presents the benefits of mobile computing and the development process of scientific and commercial applications and platforms to support them Familiarizes readers with the concepts and technologies that are successfully used in the implementation of pervasive/ubiquitous systems

Download or read book Data Architecture written by William H. Inmon and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Disciplined Agile Delivery written by Scott W. Ambler and published by IBM Press. This book was released on 2012-05-31 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master IBM’s Breakthrough DAD Process Framework for Succeeding with Agile in Large, Complex, Mission-Critical IT Projects It is widely recognized that moving from traditional to agile approaches to build software solutions is a critical source of competitive advantage. Mainstream agile approaches that are indeed suitable for small projects require significant tailoring for larger, complex enterprise projects. In Disciplined Agile Delivery, Scott W. Ambler and Mark Lines introduce IBM’s breakthrough Disciplined Agile Delivery (DAD) process framework, which describes how to do this tailoring. DAD applies a more disciplined approach to agile development by acknowledging and dealing with the realities and complexities of a portfolio of interdependent program initiatives. Ambler and Lines show how to extend Scrum with supplementary agile and lean strategies from Agile Modeling (AM), Extreme Programming (XP), Kanban, Unified Process (UP), and other proven methods to provide a hybrid approach that is adaptable to your organization’s unique needs. They candidly describe what practices work best, why they work, what the trade-offs are, and when to consider alternatives, all within the context of your situation. Disciplined Agile Delivery addresses agile practices across the entire lifecycle, from requirements, architecture, and development to delivery and governance. The authors show how these best-practice techniques fit together in an end-to-end process for successfully delivering large, complex systems--from project initiation through delivery. Coverage includes Scaling agile for mission-critical enterprise endeavors Avoiding mistakes that drive poorly run agile projects to chaos Effectively initiating an agile project Transitioning as an individual to agile Incrementally building consumable solutions Deploying agile solutions into complex production environments Leveraging DevOps, architecture, and other enterprise disciplines Adapting your governance strategy for agile projects Based on facts, research, and extensive experience, this book will be an indispensable resource for every enterprise software leader and practitioner--whether they’re seeking to optimize their existing agile/Scrum process or improve the agility of an iterative process.

Download or read book Scientific and Statistical Database Management written by Anastasia Ailamaki and published by Springer. This book was released on 2012-06-15 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 24th International Conference on Scientific and Statistical Database Management, SSDBM 2012, held in Chania, Grete, Greece, in June 2012. The 25 long and 10 short papers presented together with 2 keynotes, 1 panel, and 13 demonstration and poster papers were carefully reviewed and selected from numerous submissions. The topics covered are uncertain and probabilistic data, parallel and distributed data management, graph processing, mining multidimensional data, provenance and workflows, processing scientific queries, and support for demanding applications.