Описание: In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data.
Описание: This revised and updated edition of the bestseller provides a complete library of dimensional modeling techniques, the most comprehensive collection ever written.
Описание: Single most authoritative guide from the inventor of the technique. Presents unique modeling techniques for e-commerce, and shows strategies for optimizing performance. Companion Web site provides updates on dimensional modeling techniques, links related to sites, and source code where appropriate.
Автор: Mohanty S Название: Big Data Imperatives: Enterprise `big Data` Warehouse, `BI` ISBN: 1430248726 ISBN-13(EAN): 9781430248729 Издательство: Springer Рейтинг: Цена: 5304.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The New Information Management Paradigm
Big Data's Implication for Businesses
Big Data Implications for Information Management
Defining Big Data Architecture Characteristics
Co-Existent Architectures
Data Quality for Big Data
Data Security and Privacy Considerations for Big Data
Big Data and Analytics
Big Data Implications for Practitioners
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.
Описание: The techniques pioneered by the Kimball Group have become the industry standard for data warehouse design, development, and management. In this new edition of the Microsoft Data Warehouse Toolkit, the authors share best practices for using these techniques in SQL Server 2008 R2 and Office 2010.
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