The data collection requires an infrastructure. Responsibilities for data collection, storage, analysis, and presentation are required, as well as definitions of when, where, and how the data is collected, and how it is validated.( Bergman, Haug, and Olsen,2001).
Several steps are essential to ensure the success of the data modelling process:
- Formation of the data modelling or planning team;
- Determination of the planning tools that will be used;
- Studying user requirements and defining these through the use of data modelling diagrams; and
- Development of the database design.
A process is modelled so that it implements the business logic independent of specific endpoint properties and capabilities. It establishes the common behaviour across all endpoints for the enterprise. Its parts can always be implemented in a separate process definitions and reused within the processes implementing all the different execution paths.
The process operates on data, therefore, must contain all data that are required to implement it’s logic as well as all data that required by the endpoints. This is done in two steps – firstly, create event type and define all data necessary inside the event that are necessary for the process; then later at second stage, add more data to the event based on the data requirements from the endpoints. This data is the provided by one endpoint and required by another endpoint. The change to the event type based on the endpoint requirements does not affect the process specification because they are not accessed by the process at all.
Data and process modelling, being a process-centered approach, focuses on the flow of data and the processes that affect that data. It analyses the system’s inputs, outputs, and processes, and focus on the flow of data through the system, in order to produce a logical business information systems model. It’s easy to follow and relate to a process-centric approach.T
he three main data and process modelling techniques are DFDs, the data dictionary, and process description tools.
A data flow diagram (DFDs) is a structured, diagrammatic technique for showing the functions performed by a system and the data flowing into, out of, and within it. DFDs show the flow of data from external entities into the system, showed how the data moved from one process to another, as well as its logical storage.
The data dictionary documents the contents of data flows, data stores, external entities, and processes. In database management systems, Data Dictionary is a file that defines the basic organization of a database. A data dictionary contains a list of all files in the database, the number of records in each file, and the names and types of each field.
Describing a process unambiguously to both developer and user is a balancing act. The analyst must use methods with which a programmer is familiar, but not confuse a user. Process description tools include structured English, decision tables, and decision trees. Structured English is a subset of Standard English used to describe logical processes clearly and accurately. A decision table is a tabular description of a logical structure. A decision tree is a horizontal graphic representation of a logical structure.
The significance of data modelling is first and foremost its process-independent representation of business data, and second, it’s rapid adoption by the DBMS vendors as a viable form of data management.
