“The most popular data model in DBMS is the Relational Model. It is more scientific a model than others. This model is based on first-order predicate logic and defines a table as an n-ary relation. The main highlights of this model are:
- Data is stored in tables called relations.
- Relations can be normalized, [in which case] values saved are atomic values.
- Each row in a relation contains a unique value.
- Each column in a relation contains values from a same domain.”
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, which is based on 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 acquire the 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).
“The RDM is semantically weak ... struggles with consistent granularity and has limitations at the property level... it has no concept of data flow ... it is an incomplete theory. Great for its time but needs something better now ... it uses ill defined and linguistically suspect labels ... it has no rules for semantic accuracy ... this just makes the RDM 1% of the truth ... the RDM should have solved this all by now ... but it has clearly not. You fail to see the reality of the failure of RDM in the real world ... this is your choice. I understand why you cling to it ... it is a most excellent theory that I respect greatly ... [but o]pen minds make progress...”
Thus in a LinkedIn exchange. Criticism of the RDM almost always reflects poor foundation knowledge and lack of familiarity with the history of the field, and as we shall see, this one is not different. It is often triggered by what I call the "fad-to-fad cookbook approach", one of the latest fads being the industry's revelational "discovery" of semantics.
