What is data modeling?
The process of design and drafting a visual diagram of a system, software package, or database. It should define connections, data attributes, and flows using text, symbols and lines.
What are the types of data modeling?
The three commonly used data models are relational models, dimensional models, and entity-relationship models. Lesser used models are hierarchical, object-oriented, multi-valued, and network.
What is the data modeling process?
The six steps in the data modeling process are:
- Identify the business entities that are represented in the data set.
- Identify key properties for each entity to differentiate between them.
- Create a draft entity-relationship model to show how entities are connected.
- Identify the data attributes that need to be incorporated into the model.
- Map the attributes to entities to illustrate the data's business meaning.
- Finalize the data model and validate its accuracy.
Why is data modeling important
Data modeling is a collaborative planning process that is absolutely imperative to ensure the data model accurately reflects its intended use. Inaccuracies can lead to flaws in the database design and lead to further errors and complications.
What are the three levels of data abstraction?
The three layers of data abstraction are the concept layer, the logical layer, and the physical layer. The concept layer inspires the database by defining at a high level the elements to be modeled. The logical layer adds more detail, and is like a master blueprint that can be used to develop the model for a database. The physical layer model demonstrates the translation of the logical layer into the strict requirements of a database. Attributes identified on the logical layer, are now fully defined on the physical layer.