Data Modeling Made Simple: A Practical Guide for Business and IT Professionals, 2nd Edition by Steve Hoberman

Author:Steve Hoberman [Hoberman, Steve]
Language: eng
Format: azw3
Publisher: Technics Publications
Published: 2015-12-21T16:00:00+00:00

Modify this model to accommodate this new attribute and these three business rules. When you are done, refer to the answers section at the back of the book.

Key Points

A logical data model (LDM) represents a detailed business solution.

A relational logical data model represents how the business works. A dimensional logical data model represents what the business is monitoring.

Normalizing is a formal process of asking business questions. Normalization ensures that every attribute is a fact about the key (1NF), the whole key (2NF), and nothing but the key (3NF).

Abstraction brings flexibility to your logical data models by redefining and combining some of the attributes, entities, and relationships within the model into more generic terms.

There are a number of important terms unique to dimensional modeling including meters and dimensions.

There are different types of meters including aggregate, atomic, cumulative, and snapshot.

There are different types of dimensions including fixed dimension, degenerate, multi-valued, ragged, shrunken, and slow changing.

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