Foundations architecting data solutions von malaska ted (16 Ergebnisse)

Zustand: good. Book shows general signs of use and handling. May have light wear on the cover or edges and minimal writing or highlighting. Binding remains tight, and pages are clean and readable.

paperback. Zustand: Good. As pictured. Some wear. Very readable copy.

Zustand: acceptable. This book is in Acceptable condition. All pages are intact, but may have lots of notes, water damage or other issues and be ex library.

Zustand: New.

Paperback. Zustand: New. Big Data Solution Architecture provides everyone from CIOs and COOs to lead architects and lead developers with the fundamental concepts of big data development. Authors Ted Malaska and Jonathan Seidman guide you through all the major components necessary to start, architect, and develop successful big data projects. This practical book covers a variety of different big data architectures and applications, from massive data pipelines to web scale applications. Each chapter addresses a different part of the software development life cycle and identifies patterns that build on one another to maximize success throughout the life of your project. You'll learn how to: Build a Big Data center of excellence in your company for the first time Identify and manage risk in your data project Retain and motivate teams to increase engagement and innovation Maximize Big Data ROI and align cost structure to help your company attain success. …

Paperback. Zustand: Fair. A readable copy of the book which may include some defects such as highlighting and notes. Cover and pages may be creased and show discolouration.

Paperback or Softback. Zustand: New. Foundations for Architecting Data Solutions: Managing Successful Data Projects. Book.

Zustand: As New. Unread book in perfect condition.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Paperback. Zustand: Brand New. 225 pages. 9.25x7.00x0.50 inches. In Stock.

Zustand: New. pp. 190.

Zustand: New. pp. 190.

Paperback. Zustand: New. Big Data Solution Architecture provides everyone from CIOs and COOs to lead architects and lead developers with the fundamental concepts of big data development. Authors Ted Malaska and Jonathan Seidman guide you through all the major components necessary to start, architect, and develop successful big data projects. This practical book covers a variety of different big data architectures and applications, from massive data pipelines to web scale applications. Each chapter addresses a different part of the software development life cycle and identifies patterns that build on one another to maximize success throughout the life of your project. You'll learn how to: Build a Big Data center of excellence in your company for the first time Identify and manage risk in your data project Retain and motivate teams to increase engagement and innovation Maximize Big Data ROI and align cost structure to help your company attain success. …

Zustand: New. Big Data Solution Architecture provides everyone from CIOs and COOs to lead architects and lead developers with the fundamental concepts of big data development. Authors Ted Malaska and Jonathan Seidman guide you through all the major components necessary t.

Taschenbuch. Zustand: Neu. 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. …