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Building the Agile Database: How to Build a Successful Application Using Agile Without Sacrificing Data Management

Amazon.com Price:  $40.34 (as of 05/05/2019 15:00 PST- Details)

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Description

Is fast development the enemy of good development? Not necessarily. Agile development requires that databases are designed and built quickly enough to meet fast-based delivery schedules – but in a way that also delivers maximum business value and reuse. How can these requirements both be satisfied? This book, suitable for practitioners at all levels, will give an explanation for how to design and build enterprise-quality high-value databases within the constraints of an Agile project.

Starting with an overview of the business case for good data management practices, the book defines the quite a lot of stakeholder groups involved in the software development process, explains the economics of software development (including “time to market” vs. “time to money”), and describes an approach to Agile database development in keeping with the five PRISM principles.

This book explains how to work with application developers and other stakeholders, examines critical issues in Agile Development and Data Management, and describes how developers and data professionals can work together to make Agile projects successful whilst delivering maximum value data to the enterprise.

Building the Agile Database will serve as a very good reference for application developers, data managers, DBAs, project managers, Scrum Masters and IT managers having a look to get more value from their development efforts. Some of the topics covered:

  1. Why Agile is more than just the up to date development fad
  2. The critical distinction between the logical and physical views of data
  3. The importance of data virtualization, and how to reach it
  4. How to get rid of the “object-relational impedance mismatch”
  5. The difference between logical modeling and physical design
  6. Why databases are more than “persistence engines”
  7. When and how to do logical modeling and physical design
  8. Use of the logical data model in model-driven development
  9. Refactoring made easier
  10. Developing an “Agile Attitude”

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