Foundations for Architecting Data Solutions
Language: English
Published by O'reilly Sep 2018, 2018
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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Add to basketItem description from seller
Neuware - While many companies ponder implementation details such as distributed processing engines and algorithms for data analysis, this practical book takes a much wider view of big data development, starting with initial planning and moving diligently toward execution. Authors Ted Malaska and Jonathan Seidman guide you through the major components necessary to start, architect, and develop successful big data projects. Everyone from CIOs and COOs to lead architects and developers will explore a variety of big data architectures and applications, from massive data pipelines to web-scale applications. Each chapter addresses a piece of the software development life cycle and identifies patterns to maximize long-term success throughout the life of your project. Start the planning process by considering the key data project types. Use guidelines to evaluate and select data management solutions. Reduce risk related to technology, your team, and vague requirements. Explore system interface design using APIs, REST, and pub/sub systems. Choose the right distributed storage system for your big data system. Plan and implement metadata collections for your data architectureUse data pipelines to ensure data integrity from source to final storage. Evaluate the attributes of various engines for processing the data you collect.…
Seller Inventory # 9781492038740
- Title
- Foundations for Architecting Data Solutions
- Author
- Ted Malaska
- Publisher
- O'reilly Sep 2018
- Publication year
- 2018
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1492038741
- ISBN 13
- 9781492038740
- Item weight
- 354 grams
- Dimensions
- 231 x 176 x 11 mm
While many companies ponder implementation details such as distributed processing engines and algorithms for data analysis, this practical book takes a much wider view of big data development, starting with initial planning and moving diligently toward execution. Authors Ted Malaska and Jonathan Seidman guide you through the major components necessary to start, architect, and develop successful big data projects.
Everyone from CIOs and COOs to lead architects and developers will explore a variety of big data architectures and applications, from massive data pipelines to web-scale applications. Each chapter addresses a piece of the software development life cycle and identifies patterns to maximize long-term success throughout the life of your project.
- Start the planning process by considering the key data project types
- Use guidelines to evaluate and select data management solutions
- Reduce risk related to technology, your team, and vague requirements
- Explore system interface design using APIs, REST, and pub/sub systems
- Choose the right distributed storage system for your big data system
- Plan and implement metadata collections for your data architecture
- Use data pipelines to ensure data integrity from source to final storage
- Evaluate the attributes of various engines for processing the data you collect
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