Note: Each "Test Your Foundation Knowledge" post presents one or more misconceptions about data fundamentals. To test your knowledge, first try to detect them, then proceed to read our debunking, reflecting the current understanding of the RDM, distinct from whatever has passed for it in the industry to date. If there isn't a match, you can review references -- reflecting the current understanding of the RDM, distinct from whatever has passed for it in the industry to date -- which explain and correct the misconceptions. You can acquire further knowledge by checking out our POSTS, BOOKS, PAPERS, LINKS (or, better, organize one of our on-site SEMINARS, which can be customized to specific needs).
“Doesn't the data model come before the schema? I was tasked to build a data model and one of the resources was a schema. Isn't the schema made from the data model?”
“A data model can be different things. A schema can be a data model. Before that, there's a conceptual model, derived from the problem domain, then a logical model, capturing the entities, attributes, and relationships. After that, a schema is implemented based on those two models.”
“Yes, but if the system evolved, in practice you will have the schema (the structure of physical tables) as the ground truth, and you need to extract the logical model from it. In teaching environment of we tend to begin with the logical model and then create tables based on that.”
“this makes a little more sense to me. i thought a default data model would be out there but i can't find one. so i'm basically "recreating" one from the schema. then i assume i'll be adding on to it with third party products.”
--Reddit.com
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Misconceptions
- A data model:
- is not "different things";
- has no "default" and is not built or "recreated with third party products".
- There are no attributes in a conceptual model;
- A schema:
- is not and does not "come from" a data model;
- is not the structure of, and not extracted from physical tables.
- A logical model is not extracted from the schema.
Fundamentals
There are three types of model at three levels of representation in database management: conceptual, logical and physical. The four types of model -- conceptual, logical, physical and data -- are routinely confused and the terms used interchangeably in the industry.
While data model is used in the industry to mean "different things", it was introduced by Codd as a formal theory of data that defines a data structure, integrity and manipulation (e.g., the RDM: semantically constrained database relations and the relatonal algebra). A data model is used to formalize conceptual models of reality consisting of entity groups, properties and relationships as logical models consisting of constrained relations with attributes forming a multigroup for database representation, that can be manipulated by the relational algebra to make inferences about reality.
Data model is incorrectly used in the exchange to mean logical model and there is no such thing as a "default logical model" to be "recreated with third party products" (whatever that means). At best we might be able to say that a RDBMS implements an "abstract logical model" that can be used to produce concrete logical models that represent multiple conceptual models formally in databases.
A logical model captures the entities and groups thereof, their properties and relationships. Relations with attributes represent formally at the logical level the entity groups and entity properties at the conceptual level (i.e., at the conceptual level there are properties represented by attributes at the logical level).
Sche•ma
n. A plan, outline, or model.
n. A diagram, or graphical representation, of certain relations of a system of things, without any pretense to the correct representation of them in other respects; in the Kantian philosophy, a product of the imagination intermediate between an image and a concept. being intuitive, and so capable of being observed, like the former, and general or quasi-general, like the latter.
--Wordnik
Although a schema is used in the industry to mean either a logical model or the graphical representation thereof, it is important/useful in database management to keep them distinct in one's mind, because the latter does not usually represent all the features of the former. Avoiding the model confusion in the exchange, a logical model "comes from" the data model only in the sense that the former is used to produce the latter. The schema is just a (partial) image thereof (like the map of a geographical area). It is a visualization on a physical medium, but of a logical model -- it certainly is not extracted from the physical model. Incidentally, R-tables are also just visualizations of relations that play no part in RDM; even data in SQL tables -- which are not relations -- are not physically stored as tables.
Further Reading
Levels of Representation Conceptual Modeling, Logical Design and Physical Implementation
What Is a Data Model, and What It Is Not
Models, Models Everywhere, Nor Any Time to Think
Data Model: Neither Business, Nor Logical, Nor Physical Model
What Is a Relational Schema
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