Data Architecture: A Primer for the Data Scientist, Inmon, W.H.
Старое издание
Автор: Inmon,W.H. Название: Data Architecture: A Primer For The Data Scientist ISBN: 012802044X ISBN-13(EAN): 9780128020449 Издательство: Elsevier Science Цена: 49410 T Наличие на складе: Нет в наличии.
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: 61750.00 T 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: David Loshin Название: Big Data Analytics, ISBN: 0124173195 ISBN-13(EAN): 9780124173194 Издательство: Elsevier Science Рейтинг: Цена: 26940.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A short guide for managers to introduce big data technology to their organizations and change the culture and expectations around information management.
Автор: Ralph Hughes Название: Agile Data Warehousing Project Management, ISBN: 0123964636 ISBN-13(EAN): 9780123964632 Издательство: Elsevier Science Рейтинг: Цена: 41530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Offers an introduction to the method as you would practice it in the project room to build a data mart. This title helps to prepare you to join or lead a team in visualizing, building, and validating a single component to an enterprise data warehouse. It includes strategies for getting actionable requirements from a team`s business partner.
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Автор: David Nettleton Название: Commercial Data Mining ISBN: 0124166024 ISBN-13(EAN): 9780124166028 Издательство: Elsevier Science Рейтинг: Цена: 41530.00 T Наличие на складе: Нет в наличии. Описание: Helps you learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. This book guides you through the process from beginning to end and covers everything from business objectives to data sources, and selection to analysis and predictive modeling.
Автор: Svetla Baykoucheva Название: Managing Scientific Information And Research Data ISBN: 0081001959 ISBN-13(EAN): 9780081001950 Издательство: Elsevier Science Рейтинг: Цена: 61750.00 T Наличие на складе: Нет в наличии. Описание:
Innovative technologies are changing the way research is performed, preserved, and communicated. Managing Scientific Information and Research Data explores how these technologies are used and provides detailed analysis of the approaches and tools developed to manage scientific information and data. Following an introduction, the book is then divided into 15 chapters discussing the changes in scientific communication; new models of publishing and peer review; ethics in scientific communication; preservation of data; discovery tools; discipline-specific practices of researchers for gathering and using scientific information; academic social networks; bibliographic management tools; information literacy and the information needs of students and researchers; the involvement of academic libraries in eScience and the new opportunities it presents to librarians; and interviews with experts in scientific information and publishing.
Автор: Hsu, Hui-Huang Название: Big Data Analytics for Sensor-Network Collected Intelligence ISBN: 0128093935 ISBN-13(EAN): 9780128093931 Издательство: Elsevier Science Рейтинг: Цена: 101060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people's behaviors, and how to unobtrusively provide better services.
It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality.
In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation.
Indexing: The books of this series are submitted to EI-Compendex and SCOPUS
Contains contributions from noted scholars in computer science and electrical engineering from around the globe
Provides a broad overview of recent developments in sensor collected intelligence
Edited by a team comprised of leading thinkers in big data analytics
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