Data Modelling is the process of creating visual representation of data objects and their relationship to one another. Its normally built around business needs.
Abstract models that allow building of conceptual models and to set relationships between data items
Levels of Data Abstraction
Conceptual data models- offers a view of what the system will contain, how it will be organized and which business rules are involved.
Logical data models- Provides more detail about the concepts and relationships in the domain under consideration.
-indicates data attributes and relationship among entities.Physical data models- offers a final design that can be implemented and stored within a database, specifics on how the dat will be stored.
Data Modelling Process
The process of data modeling involves several steps, including requirements gathering, conceptual design, logical design, physical design, and implementation.
Identify the entities represented in the data set.
Identify key properties of each entity.
Identify relationship among entities.
Map attributes to entities
Assign keys as needed and decide on a degree of normalization
Finalize and validate the data model
Types of Data Models
Hierarchical data models- Each model has a singe parent which maps to one or more child tables.
Relational data models - here data models are explicitly joined using tables reducing database complexity.
Entity-relationship data models- use formal diagrams to represent the relationship between entities in a database.
Object-oriented data models- Objects are grouped in classes and have associated features.
Dimensional data models- Designed to optimize data retrieval speed for analysis in a data warehouse.
Benefits of Data Modelling
- reduce errors in database development
- Increase consistency in documentation and system design
- Improve performance and communication
- ease data mapping throughout the organization
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