Logical Data Modeling
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Identify and define business information requirements
Recognize the principles behind data architectures and corporate data models
Select an appropriate approach to data modeling
Create a logical data model
Describe the transition from a logical data model to a physical relational database design
Use advanced techniques to refine the data model
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Introduction
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Definition, benefits, and risks
Corporate vs. project data modeling
Logical vs. physical data modeling
Building the LDM
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Selecting the right approach
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Why E-R modeling?
CASE tools
E-R modeling concepts
Relationships
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Connectivity and cardinality
Optionality
Named
Many-to-many
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DSS vs. OLTP
Data warehouse
Dimensional data
Star and snowflake schema
Snowflake design issues
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Domains
Derived and calculated attributes
Multi-valued attributes
Primary and foreign keys
Normalization
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OLTP
DSS
Dimensional data
Star schema
Snowflake schema
Developing the LDM
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Dependent and associative entities
Subtypes and supertypes
Null attributes and recursive relationships
Naming objects
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