With reference to assignments 8 and 9, what characteristics does an analyst (you) examine when evaluating DFD quality? (1,500 words)

Assignment 10
SAD 1


As a review, an analyst as designer:

In designing or modeling a system, an analyst must focus on the logical view of the system and not the physical. Also an analyst must take into account on what the system is to accomplish and don’t focus on how to accomplish the system specified.


A system designer or analysts will or can convert specific requirements to optimized system design which will help programmers to convert it to database design and as well as script design. He/ she provide capabilities that make it the industry leader in the database design and data modeling market. In addition to automating all of the traditional structured methods and also features advanced database engineering, transition to object oriented design, repository extensibility, distributed repository capabilities, and model permission controls.


In what I did during the previous assignments, where I designed different data flow representation in the process of the “Pre- Enrollment in USEP”, there are certain characteristic which I evaluated in order for me to provide data flow diagrams of good quality.




As a review, DFD as a modeling tool:


The DFD portrays the system in terms of its component pieces, with all interfaces among the components indicated. Also, DFD focuses on the movement of data between external entities and processes, and between processes and data stores.


DFD is used to perform structured analysis to determine logical requirements. It is a graphical tool, useful for communicating with users, managers, and other IS personnel. It is also useful for analyzing existing as well as proposed systems and it is a relatively simple technique to learn and use.

Data Flow Diagramming is a means of representing a system at any level of detail with a graphic network of symbols showing data flows, data stores, data processes, and data sources/destinations.




Characteristics Examined in Evaluating DFD:

1. Remember
(Also commonly referred to as recognition, recall, or rote knowledge.) Be able to remember or recognize terminology, definitions, facts, ideas, materials, patterns, sequences, methodologies, principles, etc.


2. Understand
Be able to read and understand descriptions, communications, reports, tables, diagrams, directions, regulations, etc.


3. Apply
Be able to apply ideas, procedures, methods, formulas, principles, theories, etc., in job-related situations.


4. Analyze
Be able to break down information into its constituent parts and recognize the parts’ relationship to one another and how they are organized; identify sublevel factors or salient data from a complex scenario.

5. Evaluate
Be able to make judgments regarding the value of proposed ideas, solutions, methodologies, etc., by using appropriate criteria or standards to estimate accuracy, effectiveness, economic benefits, etc.


6. Create
Be able to put parts or elements together in such a way as to show a pattern or structure not clearly there before; able to identify which data or information from a complex set is appropriate to examine further or from which supported conclusions can be drawn.




Guidelines for constructing DFDs


The guidelines include the following:

1. Choose meaningful names for processes, flows, stores, and terminators.
- identify the role that the person is carrying out, rather than the person’s name or identity.

2. Number the processes.
- As a convenient way of referencing the processes in a DFD, most systems analysts number each bubble. It doesn’t matter very much how you go about doing this — left to right, top to bottom, or any other convenient pattern will do — as long as you are consistent in how you apply the numbers.

3. Redraw the DFD as many times as necessary for esthetics.
- The purpose of a DFD is to accurately model the functions that a system has to carry out and the interactions between those functions. But another purpose of the DFD is to be read and understood, not only by the systems analyst who constructed the model, but by the users who are the experts in the subject matter. This means that the DFD should be readily understood, easily absorbed, and pleasing to the eye.

4. Avoid overly complex DFDs.
- In a real-world systems analysis project, the DFD that will have to be drawn, redrawn, and redrawn again, often as many as ten times or more, before it is (1) technically correct, (2) acceptable to the user, and (3) neatly enough drawn that you wouldn’t be embarrassed to show it to the board of directors in your organization. This may seem like a lot of work, but it is well worth the effort to develop an accurate, consistent, esthetically pleasing model of the requirements of your system.

5. Make sure the DFD is internally consistent and consistent with any associated DFDs.
- a number of rules and guidelines that help ensure the dataflow diagram is consistent with the other system models — the entity-relationship diagram, the state-transition diagram, the data dictionary, and the process specification. However, there are some guidelines that we use now to ensure that the DFD itself is consistent. The major consistency guidelines are these:

* Avoid infinite sinks, bubbles that have inputs but no outputs. These are also known by systems analysts
as “black holes,” in an analogy to stars whose gravitational field is so strong that not even light can escape.

* Avoid spontaneous generation bubbles; bubbles that have outputs but no inputs are suspicious, and generally incorrect. One plausible example of an output-only bubble is a random-number generator, but it is hard to imagine any other reasonable example.

* Beware of unlabeled flows and unlabeled processes.

* Beware of read-only or write-only stores. This guideline is analogous to the guideline about input-only
and output-only processes; a typical store should have both inputs and outputs.


Why They Aren’t Called “Rules”

The most important thing to remember is that there are no hard and fast rules when it comes to producing DFDs, but there are when it comes to valid data flows. For the most accurate DFDs, you need to become intimate with the details of the use case study and functional specification. This isn’t a cakewalk necessarily, because not all of the information you need may be present. Keep in mind that if your DFD looks like a Picasso, it could be an accurate representation of your current physical system. DFDs don’t have to be art; they just have to accurately represent the actual physical system for data flow.


Some Guidelines About Valid and Non- Valid Data Flows

Before embarking on developing your own data flow diagram, there are some general guidelines you should
be aware of. Data stores are storage areas and are static or passive; therefore, having data flow directly from one data store to another doesn't make sense because neither could initiate the communication. Data stores maintain data in an internal format, while entities represent people or systems external to them. Because data from entities may not be syntactically correct or consistent, it is not a good idea to have a data flow directly between a data store and an entity, regardless of direction. Data flow between entities would be difficult because it would be impossible for the system to know about any communication between them. The only type of communication that can be modeled is that which the system is expected to know or react to. Processes on DFDs have no memory, so it would not make sense to show data flows between two asynchronous processes (between two processes that may or may not be active simultaneously) because they may respond to different external events.

Therefore, data flow should only occur in the following scenarios:
· Between a process and an entity (in either direction)
· Between a process and a data store (in either
direction)
· Between two processes that can only run
simultaneously



Data Flow Diagram Principles

* The general principle in Data Flow Diagramming is that a system can be decomposed into subsystems, and subsystems can be decomposed into lower level subsystems, and so on.
* Each subsystem represents a process or activity in which data is processed. At the lowest level, processes can no longer be decomposed.
* Each 'process' (and from now on, by 'process' we mean subsystem and activity) in a DFD has the characteristics of a system.
* Just as a system must have input and output (if it is not dead), so a process must have input and output.
* Data enters the system from the environment; data flows between processes within the system; and data is produced as output from the system


1. A system can be decomposed into subsystems, and
subsystems can be further decomposed into lower level
subsystems.
2. Each subsystem represents a process or activity in which
data is processed.
3. At the lowest level, processes can no longer be decomposed.
4. Each 'process' has the characteristics of a system. A process
must have input and output.
5. Data enters the system from the environment, data flows
between processes within the system and data is produced
as output from the system.



Data Flow Diagram Rules

1. Any data flow leaving a process must be based on data that
are input to the process.
2. All data flows are named and the name reflects the data
flowing between processes, data stores, sources, or sinks.
3. Only data needed to perform the process should be an input
to the process.
4. A process should know nothing about, that is, be
independent of, any other process in the system, it should




References:

http://www.asq.org/certification/quality-process-analyst/bok.html
http://www.cmp.jobs/qa-analyst-1153.php
http://spot.colorado.edu/~kozar/DFDtechnique.html