Too many business systems go wrong due to poor design. One design element that needs to be taken seriously is the flow of data. This refers to the understanding of the movement of data through a system comprised of software, hardware or a combination of both.
Data flows are an important design element for business information systems. Getting the data flow correct means that complications can be avoided for the user.in addition, a correctly sequences data flow allows issues of data security and data integrity to be addressed. In some sectors, such as pharmaceuticals, adherence to data integrity principles is a core requirement of Good Manufacturing Practice (GMP).
The concept of the data flow is not new (Tom DeMarco put forward the concept diagrammatically as part of structured analysis in 1979); however, many businesses neglect to map out their data sufficiently before purchasing, designing, validating and implementing their technologies.
On developing a new computerised system, mapping the data flow should be one of the first activities undertaken. This enables the system to be built around the optimal data path. The flow should be a dynamic document, updated as the system is configured. Once established and the system is in use, any device updates that could later the data flow should be subject to an appropriate controlled change.
A data-flow diagram is the best way of representing a flow of data through a process or a system. Such a diagram will provide information about the outputs and inputs of each entity and the process itself. The diagram is a form of flowchart.
When developing such diagrams, simplicity is important. Hence, for complex systems it is best to avoid undertaking everything in one dataflow. A single, complex dataflow will make the data transformation aspect of the computerised system design longer, it also makes it harder to understand and reuse the dataflow. Therefore, breaking your dataflow into multiple dataflows is recommended.
Risk assessment tools can also be useful for understanding data paths and what the different implications are at each stage. A mature data governance system adopts a ‘risk management’ approach across all areas of the quality system.
Checking and rechecking are also necessary, as an incorrect diagram can create serious errors. Examples of errors include forgetting to include a data flow or pointing an arrow in the wrong direction.
A key reason why keeping data flow diagrams up-to-date is to address issues of system growth. As data volume continues to grow, so does the challenge of wrangling that data into well-formed, actionable information. Without clear data flow maps, and where flows are not updated, this leads to situations where analytics becomes increasingly challenging and computerised systems cannot be sufficiently challenged in order to extract data of value.
Another reason why data flows are important is in relation to the emergent privacy laws, as with GDPR in the European Union and the increasing number of states in the U.S. that are adopting consumer facing legislation. To comply with such regulations, understanding how data moves around business systems is essential.
