Titolo: Agile Data Warehousing for the Enterprise : A Guide for Solution Architects and Project Leaders
Editore: Morgan Kaufmann
Data di pubblicazione: 2015
Lingua: Inglese
ISBN 10: 0123964644
ISBN 13: 9780123964649
Rilegatura: Brossura
Condizione: As New

Descrizione articolo

Riassunto

Building upon his earlier book that detailed agile data warehousing programming techniques for the Scrum master, Ralph's latest work illustrates the agile interpretations of the remaining software engineering disciplines:

Requirements management benefits from streamlined templates that not only define projects quickly, but ensure nothing essential is overlooked.
Data engineering receives two new "hyper modeling" techniques, yielding data warehouses that can be easily adapted when requirements change without having to invest in ruinously expensive data-conversion programs.
Quality assurance advances with not only a stereoscopic top-down and bottom-up planning method, but also the incorporation of the latest in automated test engines.

Use this step-by-step guide to deepen your own application development skills through self-study, show your teammates the world's fastest and most reliable techniques for creating business intelligence systems, or ensure that the IT department working for you is building your next decision support system the right way.

Learn how to quickly define scope and architecture before programming starts
Includes techniques of process and data engineering that enable iterative and incremental delivery
Demonstrates how to plan and execute quality assurance plans and includes a guide to continuous integration and automated regression testing
Presents program management strategies for coordinating multiple agile data mart projects so that over time an enterprise data warehouse emerges
Use the provided 120-day road map to establish a robust, agile data warehousing program

Dalla quarta di copertina

Requirements management benefits from streamlined templates that not only define projects quickly, but ensure nothing essential is overlooked.
Data engineering receives two new "hyper modeling" techniques, yielding data warehouses that can be easily adapted when requirements change without having to invest in ruinously expensive data-conversion programs.
Quality assurance advances with not only a stereoscopic top-down and bottom-up planning method, but also the incorporation of the latest in automated test engines.

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