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A data flow model shows where information comes from, how a system processes or transforms it, where it is stored, and where it goes. In systems analysis, this usually means a data-flow diagram (DFD): a visual account of data moving among people, processes, systems, and stores. It describes information movement, not every detail of the system’s control logic or implementation.
What a data flow model means
The phrase “data flow model” is used here in the data-flow-diagram sense. A DFD answers a practical question: what data moves between which people or systems, through what processes, and into or out of which stores? The UK Health Security Agency describes a DFD as “a visualisation tool used to illustrate how information flows through a process or system.” UK Health Security Agency guidance
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The term can be confused with a data model. A data model describes the structure of stored information—such as entities, attributes, and relationships. A DFD instead shows movement and processing. They can complement each other, but they answer different questions.
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A DFD is built from four kinds of elements. Their exact symbols depend on the notation family, but their roles are consistent.
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- External entities: People, organizations, or systems outside the process being modeled that provide data or receive it.
- Processes: Activities that transform, evaluate, or otherwise act on data.
- Data stores: Places where data is held, such as a file or database.
- Data flows: Arrows showing data moving between entities, processes, and stores.
For example, an insurance-claim DFD might show a customer submitting claim details, a process evaluating the claim, a store holding the claim record, and an insurer receiving a decision or outcome.
Notation: choose one symbol system
Yourdon/DeMarco and Gane/Sarson are two recognized DFD notation families. In Yourdon/DeMarco, processes are circles, external entities are squares or rectangles, and stores are parallel lines. In Gane/Sarson, processes are rounded rectangles and stores are open-ended rectangles. Both use arrows for data flows, and external entities are represented similarly. UK Health Security Agency notation guidance
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Choose one family for a diagram and use it consistently. Mixing symbols without explanation can make readers unsure whether the symbols mean different things or simply come from different conventions.
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Levels of detail: from context to decomposition
Begin with a context-level view: draw the system boundary and show the external people, organizations, or systems that exchange data with it. This gives readers an overview before they encounter internal detail. The Federal Highway Administration describes a Level 0 DFD as the most general picture of data flow through a system, with lower levels adding detail. Numbering conventions can vary by method, so identify the convention you are using rather than assuming all organizations use the same levels. Federal Highway Administration DFD appendix
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Decompose a major process into a lower-level diagram only when the overview hides information the intended audience needs. A large diagram is not automatically a more useful one: keep each view readable and make sure it agrees with other descriptions of the system. UK Health Security Agency guidance on decomposition
What to include in a useful model
For a processing application, trace the data from input to outcome. Identify who or what supplies each input, which process changes or evaluates it, whether a resulting record is stored, and who or what receives the output. Make the system boundary clear so readers can distinguish internal processes and stores from outside participants.
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For architecture or data-governance work, add annotations that help explain the data’s handling when those details matter. Microsoft Learn recommends highlighting data classification—such as public, confidential, or regulated—and whether movement is batch, streaming, or near real time. Microsoft Learn architecture guidance
When reviewing two DFDs, first check that they cover the same system boundary and audience. Then compare their notation, level of detail, represented entities and flows, relevant data-handling annotations, and consistency with related system descriptions. A comparison is meaningful only when the diagrams are intended to describe comparable scope.
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Logical and physical data flow views
A logical DFD focuses on the information-processing work: what data enters, what the system does with it, and what leaves. It avoids committing to particular implementation components. A physical DFD shows the actual components or arrangements involved, such as where processing or storage takes place. State how much implementation detail the diagram includes; usage of these labels and conventions can vary. IBM’s DFD overview
What a DFD does not show by itself
A DFD emphasizes data movement and the processes acting on data. It does not, by itself, fully specify the sequence of program or manual steps, timing, database structure, or deployment arrangement. A flowchart is better suited to showing a sequence of steps; a data model describes stored-data structure; and an architecture diagram can communicate implementation or deployment. Use the view that answers the question at hand, or combine complementary diagrams when readers need several perspectives. The Federal Highway Administration distinguishes DFDs from flowcharts, while Microsoft Learn treats DFDs as one kind of architecture design diagram. FHWA DFD appendix · Microsoft Learn architecture guidance
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