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Data Architecture for Software Architects (A Guide to Building Data-Driven Systems)

List Price: $69.99
SKU:
9781098181192
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25 unit(s)
Expected release date is May 4th 2027
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  • Product Details

    Author:
    Pramod Sadalage, Premanand Chandrasekaran
    Format:
    Paperback
    Pages:
    350
    Publisher:
    O'Reilly Media (May 4, 2027)
    Imprint:
    O'Reilly Media
    Release Date:
    May 4, 2027
    Language:
    English
    ISBN-13:
    9781098181192
    ISBN-10:
    1098181190
    Weight:
    16oz
    Dimensions:
    7" x 9.19"
    File:
    TWO RIVERS-PERSEUS-Metadata_Only_Perseus_Distribution_Customer_Group_Metadata_20260826163418-20260826.xml
    Folder:
    TWO RIVERS
    List Price:
    $69.99
    Country of Origin:
    United States
    Pub Discount:
    60
    Case Pack:
    18
    As low as:
    $60.19
    Publisher Identifier:
    P-PER
    Discount Code:
    C
  • Overview

    In today's interconnected software landscape, understanding data architecture is essential for building efficient, modern systems. Software architects, engineers, and data professionals alike need tools to design and evolve architectures to effectively handle and act on vast amounts of data. This book offers you a comprehensive exploration of operational and analytical data architectures, the trade-offs involved, and when it's time to migrate to a new style.

    Packed with practical advice, authors Pramod Sadalage and Premanand Chandrasekaran help readers make informed decisions about moving, storing, and processing data at scale to meet business needs, end user demands, and maintainer requirements. Learn how to partition data, manage reporting and caching in operational systems, and structure your architecture to ensure accessibility and efficiency. Whether you're designing from scratch or modernizing an existing system, this is the resource you need to make thoughtful, future-proof choices.

    • Understand why data architecture is critical for modern software systems
    • Explore operational and analytical data architecture styles and their uses
    • Identify the key trade-offs in choosing or updating your architecture
    • Migrate data architectures effectively to support new demands
    • Implement strategies for data partitioning, reporting, and caching