A data flow diagram or DFD is an effective tool to represent the flow of data within the system, simplifying the comprehension of processes. Since DFDs exhibit data flow, in/out data, and processes engaged with these flows, it is useful to see how data flows through a system and what interactions and dependencies are significant. These are highly useful to anyone in system design, business operations, or statistics.
This article defines data flow diagrams and explains their use, elements, and general procedures for constructing DFDs. The details are highly useful to the student performing systems analysis, the IT professional generating DFDs for practical uses, and any individual wishing to fully understand how to employ DFDs in any project.
In this article
Part 1: What Is a Data Flow Diagram?
A Data Flow Diagram (DFD) is a high-level block diagram depicting application processing as data flows. It shows the flow of data between the processes and data stores and the entities outside the system, making one understand how a system works.
Structured like a function in programming, DFD focuses on the path of data, which acts as a tool for systems study and planning. The diagram assists in locating areas that require improvement, shedding light on the fact that some elements in a system are unnecessary or cause delays within a system.
Characteristics of DFDs
The following are the main characteristics of DFDs:
- Clarity and simplicity: In DFDs, functionalities are excluded, and such operations are incorporated into other forms to increase the accessibility of the data.
- Systematic approach: Structured methods help write down systematically the data processing tasks within a system, hence helping to improve the order levels.
- Scalability: DFDs are versatile and can be created with more or less depth depending on the need.
- Communication tool: It also makes the system analysis and design efficient since everyone involved in the project has the same picture of what is expected of them.
Part 2: History of Data Flow Diagrams
DFDs originated in the early 1970s by Larry Constantine, one of the pioneers in software engineering. Constantine introduced the DFD as part of the Structured Design methodology, which offers clean and straightforward methods for modeling systems.
In 1979, Tom DeMarco expanded the understanding of the status of DFDs in his book “Structured Analysis and System Specification,” which marked DFDs as a primary tool in system analysis and design.
Since then, DFDs have progressed and are now well-accepted and frequently used in most industries to document and analyze information systems in the SE domain.
Part 3: Symbol and Notation Used in the DFD
Many DFDs use a set of signs and conventions to represent various aspects of a system. Every symbol has its meaning, which helps maintain uniformity and achieves the objectives of the diagram.
External Entity
External entities, also called terminators or source/sink, represent the outside world of a particular system. These can be regarded as data sources or destinations.
They are the external users of the system who can either feed information into the system or receive data from it. Externals are often represented by rectangles or squares on a business model canvas.
Process
Functions or activities are the actual events or transformations that convert input data into output data. They are the fundamental elements of a DFD in data processing. Activities are generally illustrated as ovals or rounded rectangles.
Datastore
We can define data stores occupying the places or sections within the system encompassing data. They are shown as rectangles that can be continued indefinitely or two parallel straight lines. Datastores depict where data is located; it could be a file or any other storage entity in a database.
Data Flow
Data flow arrows refer to the transfer of data from the processes, through the data stores, and to outside entities. These symbolize the data flow, indicating how the data goes in a particular system. Lines or simple arrows commonly represent the direction of data flow arrows.
Part 4: Types of Data Flow Diagrams
Data Flow Diagrams (DFDs) come in two main types: Logical DFDs and Physical DFDs. These models fit into a particular position in system analysis and design activity.
Logical DFD
A Logical DFD mainly looks at the business context and how the business domain functions. It explains how the system is built and represents the flow, activities, and data repositories within and about the system.
This kind of DFD is feasible in critically comprehending business services, data necessities, and segment correlations.
Physical DFD
While a Logical DFD focuses on the business process, a Physical DFD offers more information about implementation. The area includes the hardware and software elements, the files and records in the system, and the people who have access to the system.
This DFD benefits the system designers and developers as it defines the authentic data flow and processes and illustrates the technological aspects of the system implementation.
Part 5: Use Cases of Data Flow Diagram
DFDs, or data flow diagrams, are among the most popular diagrams needed in different fields to improve system design, manage processes, and analyze data.
- Software engineering: DFDs provide a systemic method of analyzing and mapping data movement between various system components. These represent the logic paths of information and are used to support various software applications.
- Business management: It offers the best approach to showing managers how data moves within an organization so that they can correct the flow and make better decisions from it, thus improving productivity.
- Database development: DFDs assist database designers in knowing how data is obtained, processed, and retrieved efficiently in any database established by determining related entities.
- Agile development: In SDLC, the agile teams use DFD diagrams to represent the data flow in several iterative phases. DFDs facilitate collaboration by showing data flow and key inputs and outputs for understanding requirements, sprint planning, and responding to changes.
- System structures: The DFDs are commonly employed by system architects to design and document the structures of complex systems. They look for potential problems and determine good data paths to resolve system growth and sustainability concerns.
- Product management: DFD diagrams are also applied by product managers for various purposes, such as defining product features and enhancing the product's overall user experience. They help achieve cohesion between the requirement and development processes for a smoother workflow.
- Data analytics: DFDs assist the analysts in comprehending the aspects of data gathering, transformation, and application. They create optimized routes for data to be processed and cleansed and thus render data insightful.
- Growth teams: DFDs that describe data flows connected with users’ interactions allow for defining critical points and using data-driven techniques for development.
Part 6: How to Create a Data Flow Diagram in General?
Step 1:
Determine where the system you are analyzing starts and where it ends. Decide which processes will be included and at what points the system interfaces with other systems.
Step 2:
List all the processes used, the data repositories in which the data is kept, and all other entities that operate outside the system.
Step 3:
Define how data flows from one process to a data store and other entities. Each data flow must be described using an indicator showing the exchange data.
Step 4:
The initial DFD should be at a high level and is called a context diagram; in this diagram, the system is depicted as a single process interacting with other entities.
Step 5:
Subdivide the high-level DFD into more detailed DFDs. These six process steps can, in turn, be further broken down into sub-processes to give further insight into the system.
Step 6:
Mostly, circles represent the process; rectangles symbolize the external entity. The open-ended rectangle represents the data stores, and arrowheads depict data flows to prepare the DFD.
Step 7:
Seek stakeholders’ approval on the DFD to confirm the created representation of the system is accurate.
Part 7: Tips for Creating Data Flow Diagram
Before starting to create a data flow diagram, keep these guidelines in mind:
- Use clear labels: Make sure everything involved in the processes, namely the stored data and data movements, has accompanying labels.
- Keep it simple: Ensure that the DFD is concise and does not have complex details. Do not crowd the diagram with unnecessary information, which can easily clutter the design.
- Iterate and improve: You should ensure this DFD is constantly reviewed and updated to be as precise and present as much detail as possible.
- Use standard symbols: Sticking to standard symbols displayed in DFDs is recommended to enhance their readability and reduce confusion.
- Avoid redundancies: Avoid including repetitive activities or data transfers that are not necessary from the overall understanding of the system.
- Don't ignore stakeholder input: It is important to confirm the DFD with the stakeholders to ensure it has captured their understanding and specifications.
- Don’t overcomplicate: Do not pad the diagram with trivial information, which would only overcrowd the picture and be ineffective.
Conclusion
Data Flow Diagrams (DFDs) are handy and effective in representing and analyzing data movement in systems. This writing explored the creation of DFDs, their evolution, and the kinds of DFDs, symbols, and applications in diverse industries.
Also, it described how to construct proper DFDs step-by-step and outlined proper recommendations to do it. Learning to read and create DFDs enables professionals to advance the system’s design, refine processes, and optimize data utilization.
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