Research any topic before you write.

Find related topics. | Discover entities. | See connections. | Build a topical map.

Data modeling

Data modeling in software engineering is the process of creating a data model for an information system by applying certain formal techniques. It may be applied as part of broader model-driven engineering (MDE) concept.

Art, Technology & Products

Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.

Research this topic

Explore the main themes, entities and connections around Data modeling. Start with the topic map, then use the sections below for research and deeper semantic analysis.

Explore this topic

Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.

Topics to explore

Browse the full topic structure. Each item opens a new analysis centered on that subject.

Overview

Topics

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

Map overview Semantic statistics

Data modeling

Nodes60
Edges59
Triples95
Avg. degree1.97
Density0.033333
Components1

How this topic connects Entity context

See the strongest relationship patterns around the current topic before diving into the raw triples.

Data modeling

Top relations

related to Further reading · 38
Data modeling → Advances, Alan Chmura, April, Archived, Bekke, Classification, Data Analysis, Data Modeling Essentials'Matthew West, Data ModelingGraeme, Developing High Quality Data, Do, Graham, Johannes Hendrikus, John Vincent Carlis, Joseph, June, Lawrence Sanders, Logical Data Modeling, Maguire, Mark Heumann
related to External links · 16
Data modeling → Agile/Evolutionary Data ModelingData, Archived March, Chris Bradley, Chris BradleyData Modeling, DBMS's Part, Development, IMM, Information Management Metamodel, Methodologies, Modeling Archived March, NOT, Object Management GroupData Modeling, Tony DrewryRequest For Proposal, UMLData Modeling, Wayback Machine Notes, Wayback MachineDatabase Modelling
see also · 14
Data modeling → Approach, Architectural, Comparison, Data Model, Discrete, Framework, High, Open, Organisational, Process, Set, Software, Structure, Type
related to Data modeling process · 7
Data modeling → Data Definition Language, Database Management System, DBMS, However, In, Principally, The
related to Entity–relationship diagrams · 6
Data modeling → An, Entity, ERM, The, There, These
related to Semantic data modeling · 6
Data modeling → As, DBMS, That, The, Therefore, Thus
related to overview · 5
Data modeling → Data, Implementation, The, There, Therefore

Important terminology Word statistics

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

data model modeling models information systems used logical database conceptual business system process may within requirements interfaces semantic schema physical

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
a 'classification relation'instance ofa generic data model may define relation types0.80text
being a binary relation between an individual thinginstance ofa generic data model may define relation types0.80text
a kind of thinginstance ofa generic data model may define relation types0.80text
Data modelingrelated to Data modeling processIn0.60section
Data modelingrelated to Data modeling processThe0.60section
Data modelingrelated to Data modeling processData Definition Language0.60section
Data modelingrelated to Data modeling processPrincipally0.60section
Data modelingrelated to Data modeling processHowever0.60section
Data modelingrelated to Data modeling processDatabase Management System0.60section
Data modelingrelated to Data modeling processDBMS0.60section
Data modelingrelated to Entity–relationship diagramsThere0.60section
Data modelingrelated to Entity–relationship diagramsThe0.60section

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

    Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.

    Min side: 3
    For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.