データ移動管理 Managing Data in Motion : Data Integration Best Practice Techniques and Technologies (The Morgan Kaufmann Series on Business Intelligence)

データ移動管理<br>Managing Data in Motion : Data Integration Best Practice Techniques and Technologies (The Morgan Kaufmann Series on Business Intelligence)

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データ移動管理
Managing Data in Motion : Data Integration Best Practice Techniques and Technologies (The Morgan Kaufmann Series on Business Intelligence)

Reeve, April

ウェブストア価格 ¥10,408（本体¥9,462）
Morgan Kaufmann Publishers In（2013/04発売）
外貨定価 US$ 49.95
ポイント 94pt

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製本 Paperback:紙装版/ペーパーバック版／ページ数 204 p.
言語 ENG
商品コード 9780123971678
DDC分類 005.74

基本説明

Presents a vendor-neutral overview of the different technologies and techniques for moving data between computer systems.

Full Description

Managing Data in Motion describes techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling scalable architectures. Author April Reeve brings over two decades of experience to present a vendor-neutral approach to moving data between computing environments and systems. Readers will learn the techniques, technologies, and best practices for managing the passage of data between computer systems and integrating disparate data together in an enterprise environment.

The average enterprise's computing environment is comprised of hundreds to thousands computer systems that have been built, purchased, and acquired over time. The data from these various systems needs to be integrated for reporting and analysis, shared for business transaction processing, and converted from one format to another when old systems are replaced and new systems are acquired.

The management of the "data in motion" in organizations is rapidly becoming one of the biggest concerns for business and IT management. Data warehousing and conversion, real-time data integration, and cloud and "big data" applications are just a few of the challenges facing organizations and businesses today. Managing Data in Motion tackles these and other topics in a style easily understood by business and IT managers as well as programmers and architects.

Part 1: An Introduction to Data Integration

Part 2: Batch Data Integration

• ETL

• Data Warehousing

• Data Conversion

• Batch Data Integration Architecture and Metadata

Part 3: Real-Time Data Integration

• Best Practice Patterns

• Technologies

• Message Modeling

• XML

• Master Data Management

• Real Time Data Integration Architecture and Metadata

• Interactions with Legacy Applications

• External Interaction

Part 4: Cloud and Big Data Integration