Explain DFD & Data Dictionary? Explain in detail how the information requirement is determined for an organization?


A data dictionary is a structured repository of data about data. It is a set of rigorous definitions of all DFD data elements and data structures. Most of the data flow in the DFD are specified here. Some of the most obvious ones are not shown here. The data dictionary entry for weekly timesheet specifies that this data flow is composed of three basic data entities - the employee name, employee ID and many occurrences of the two - tuple consisting of regular hours and overtime hours. The data dictionary for this DFD is shown below:
Weekly timesheet = Emplyee_Name + Employee_ID + {Regular_hours + overtime_hours}
Pay_rate = {Horly | Daily | Weekly} + Dollar_amount
Employee_Name = Last + First + Middle_Initial
Employee_ID = digit + digit + digit + digit
Once we have constructed a DFD and its associated data dictionary, we have to somehow verify that they are "correct". There can be no formal verification of a DFD, because what the DFD is modeling is not formally specify anywhere against which verification can be done. Human processes and rule of thumb must be used for verification. In addition to the walkthrough with the client, the analyst should look for common errors. Some common errors are
1.      Unlabeled data flows.
2.      Missing data flows: Information required by a process is not available.
3.      Extraneous data flows: Some information is not bein used in the process
4.      Consistency not maintained during refinement
5.      Missing processes
6.      Contains some control information
The DFDs should be carefully scrutinized to make sure that all the processes in the physical environment are shown in the DFD. It should also be ensured that none of the data flows is actually carrying control information.

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