Data Modeling - Time for a Change
In parallel with this, educational psychologists developed concept mapping.
Adding psychology to the equation means that data modeling is not a done deal. If you are looking for a modern approach to data modeling, keep reading!
Graph data modeling is a technique superior to traditional data modeling for both relational and graph, document, key-value, leveraging cognitive psychology to improve big data designs.
- Agile everything
- The rise of Knowledge Graphs
- SQL is going to add a property graph extension and a new graph query language
- The tried and trusted RDF / OWL stack is being extended in the direction of property graphs
If anybody has given the legacy ways an irreversible "enough is enough", then his name is Dave McComb. See the reference to his book "Software Wasteland" here on this page.
Introducing Graph Data Modeling
Graph Data Modeling is for You, if You …
- need to model data for graph databases, or, for that matter, SQL (yes, indeed)
- work in analytics, big data and/or data science and must visualize data structures
- develop data models as you go
- think “There must be a better way than classic data modeling"
There are 3 ways to learn more about graph data modeling
How to explore the business context and map the meaning and the structure.
Business Concept Modeling explained.
Business / conceptual level.
Data Modeling Requirements.
Graph Data Modeling explained.
Logical and physical levels.
The History of Data Modeling