Why this is in my collection

From the publisher:

Information Systems are a synthesis of complex components where data plays a critical role. Data Modeling requires a disciplined approach making use of business and technical knowledge. Using data models for database design, implementation, and maintenance requires the implementation of procedures that will secure successful database deployment and validation. This book teaches you the basic technical knowledge required for physical data modeling as well as procedures for model implementation and maintenance. With examples in two major Relational Database Management Systems (Oracle and DB2) th

Highlights

  • The model-based environment as an operating discipline — Pantic's subject is not drawing diagrams but running a whole implementation lifecycle from the model in PowerDesigner; this is proto-MDDE from the 2013 tooling era: the model as the working artifact, not the documentation of one.
  • Procedures around the model are what make it trustworthy — the book insists that deployment and validation need defined, repeatable procedures, not craftsmanship per release; process rules wrapped around a model are precisely the model + rules pairing that survives platform churn.
  • Physical modeling is where the model meets consequence — the disciplined path from logical intent to DBMS-specific physical design (Oracle and DB2 in the examples) is the step most teams improvise; making it procedural is what later made it generatable.
  • Model maintenance is a first-class activity — a model that is not maintained alongside the database it produced becomes fiction within months; the drift problem is the strongest practical argument for generating the implementation from the model instead of beside it.
  • Business and technical knowledge must meet in the model — data modeling is framed as a synthesis discipline, requiring both what the business means and what the engine can do; the same dual literacy Data Vault demands at business-key time.
  • Tool-specific, principle-general — the examples are PowerDesigner, Oracle, and DB2, and all three have faded from the center of the stack, yet the procedures translate intact; a neat demonstration that the modeling layer outlives the platforms underneath it.

Highlights on this page are generated with the help of AI.