Описание: This revised and updated edition of the bestseller provides a complete library of dimensional modeling techniques, the most comprehensive collection ever written.
Автор: Carsten Dittmar Название: Knowledge Warehouse ISBN: 382448126X ISBN-13(EAN): 9783824481262 Издательство: Springer Рейтинг: Цена: 7978.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Es baut auf dem Data Warehouse auf, uberwindet aber dessen Defizite und ermoeglicht die sinnvolle Integration bisher isolierter Theoriefelder, die sich mit dem Phanomen des Lernens auf multipersoneller Ebene und mit dem Management der Ressource Wissen auseinandersetzen.
Автор: Wolfgang Behme; Harry Mucksch Название: Data Warehouse-gest?tzte Anwendungen ISBN: 3409116591 ISBN-13(EAN): 9783409116596 Издательство: Springer Рейтинг: Цена: 5129.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In Ergдnzung zu ihrem bereits in der 4. Auflage erscheinenden Buch zum Data Warehouse-Konzept widmen sich die Autoren hier ganz der Beschreibung verschiedener Anwendungsmцglichkeiten. Der Nutzen eines Data Warehouses entsteht nicht in erster Linie durch die Speicherung, sondern vielmehr erst durch die zielgerichtete Aufarbeitung und Analyse der Informationen. Dieses fьhrt zu einer Fьlle von Einsatzmцglichkeiten (wie z.B. Balanced Scorecards oder Data Mining-Auswertungen zur Vorhersage von Gasverbrдuchen), die fьr Unternehmen gewinnbringend genutzt werden kцnnen.
Автор: Naveen Prakash; Deepika Prakash Название: Data Warehouse Requirements Engineering ISBN: 9811070180 ISBN-13(EAN): 9789811070181 Издательство: Springer Рейтинг: Цена: 10366.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: As the first to focus on the issue of Data Warehouse Requirements Engineering, this book introduces a model-driven requirements process used to identify requirements granules and incrementally develop data warehouse fragments. In addition, it presents an approach to the pair-wise integration of requirements granules for consolidating multiple data warehouse fragments. The process is systematic and does away with the fuzziness associated with existing techniques. Thus, consolidation is treated as a requirements engineering issue.The notion of a decision occupies a central position in the decision-based approach. On one hand, information relevant to a decision must be elicited from stakeholders; modeled; and transformed into multi-dimensional form. On the other, decisions themselves are to be obtained from decision applications. For the former, the authors introduce a suite of information elicitation techniques specific to data warehousing. This information is subsequently converted into multi-dimensional form. For the latter, not only are decisions obtained from decision applications for managing operational businesses, but also from applications for formulating business policies and for defining rules for enforcing policies, respectively. In this context, the book presents a broad range of models, tools and techniques. For readers from academia, the book identifies the scientific/technological problems it addresses and provides cogent arguments for the proposed solutions; for readers from industry, it presents an approach for ensuring that the product meets its requirements while ensuring low lead times in delivery.
Автор: Dan Linstedt Название: Building a Scalable Data Warehouse with Data Vault 2.0 ISBN: 0128025107 ISBN-13(EAN): 9780128025109 Издательство: Elsevier Science Рейтинг: Цена: 9262.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
TheData 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
Автор: Hultgren Hans Название: Modeling the Agile Data Warehouse with Data Vault ISBN: 061572308X ISBN-13(EAN): 9780615723082 Издательство: Неизвестно Цена: 13622.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Silvers, Fon Название: Building and Maintaining a Data Warehouse ISBN: 0367387646 ISBN-13(EAN): 9780367387648 Издательство: Taylor&Francis Рейтинг: Цена: 8726.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: As it is with building a house, most of the work necessary to build a data warehouse is neither visible nor obvious when looking at the completed product. While it may be easy to plan for a data warehouse that incorporates all the right concepts, taking the steps needed to create a warehouse that is as functional and user-friendly as it is theoretically sound, is not especially easy. That's the challenge that Building and Maintaininga Data Warehouse answers.
Based on a foundation of industry-accepted principles, this work provides an easy-to-follow approach that is cohesive and holistic. By offering the perspective of a successful data warehouse, as well as that of a failed one, this workdetails those factors that must be accomplished and those that are best avoided.
Organized to logically progress from more general to specific information, this valuable guide:
Presents areas of a data warehouse individually and in sequence, showing how each piece becomes a working part of the whole
Examines the concepts and principles that are at the foundation of every successful data warehouse
Explains how to recognize and attend to problematic gaps in an established data warehouse
Provides the big picture perspective that planners and executives require
Those considering the planning and creation of a data warehouse, as well as those who've already built one will profit greatly from the insights garnered by the author during his years of creating and gathering information on state-of-the-art data warehouses that are accessible, convenient, and reliable.
Автор: Inmon, W.H. Название: Data Architecture: A Primer for the Data Scientist ISBN: 0128169168 ISBN-13(EAN): 9780128169162 Издательство: Elsevier Science Рейтинг: Цена: 9262.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
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
Автор: W. H. Inmon Название: Building the Data Warehouse, 4th Edition ISBN: 0764599445 ISBN-13(EAN): 9780764599446 Издательство: Wiley Рейтинг: Цена: 5861.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Explains the fundamentals of data warehouse systems. This book covers topics such as methods for handling unstructured data in a data warehouse and storing data across multiple storage media, and discusses the pros and cons of relational versus multidimensional design, and how to measure return on investment in planning data warehouse projects.
Автор: Rainardi, Vincent Название: Building a data warehouse ISBN: 1430211962 ISBN-13(EAN): 9781430211969 Издательство: Springer Рейтинг: Цена: 8878.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Here is the ideal field guide for data warehousing implementation. Coverage then explains how to populate the data warehouse and explores how to present data to users using reports and multidimensional databases and how to use the data in the data warehouse for business intelligence, customer relationship management, and other purposes.
Описание: This book describes warehouse-scale computers (WSCs), the computing platforms that power cloud computing and all the great web services we use every day. It discusses how these new systems treat the datacenter itself as one massive computer designed at warehouse scale, with hardware and software working in concert to deliver good levels of internet service performance. The book details the architecture of WSCs and covers the main factors influencing their design, operation, and cost structure, and the characteristics of their software base. Each chapter contains multiple real-world examples, including detailed case studies and previously unpublished details of the infrastructure used to power Google's online services. Targeted at the architects and programmers of today's WSCs, this book provides a great foundation for those looking to innovate in this fascinating and important area, but the material will also be broadly interesting to those who just want to understand the infrastructure powering the internet.The third edition reflects four years of advancements since the previous edition and nearly doubles the number of pictures and figures. New topics range from additional workloads like video streaming, machine learning, and public cloud to specialized silicon accelerators, storage and network building blocks, and a revised discussion of data center power and cooling, and uptime. Further discussions of emerging trends and opportunities ensure that this revised edition will remain an essential resource for educators and professionals working on the next generation of WSCs.
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