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Three Approaches for the Requirement analysis

The business analyst gathers the project information or business requirements from the client and shares them with the IT team. A detailed analysis of the requirements is provided by the business analyst using different approaches listed below:

  1. State and project concepts
  2. Data flow diagrams
  3. Entity relationship diagrams

The approaches for requirements analysis are explained in detail as below: 

State VS project

State will be given by the system which suggests that the system is operating at some specified condition. This condition is given by the system which has existent in one of the several states of the operation.

Data flow diagrams(DFD)

These are referred to as the data flow graphs or bubble charts, DFD will depute the flow of the data through the sequence of processing steps or the transformation in the system. These are used in the problem analysis and also document a software design. This will assist the potential system users to participate in validating the analysis.

Basic notations which are used to represent DFD is been shown:

  1. bubbles or circle or semi rounds rectangle which indicate process transformer of the data.                                        
  2. Arrow which indicates annotated with data name
  3. Producer or the consumer of information data which reside
  4. Outside the bounds of the system.
  5. Rectangles which represents the data source or data store which will be used by one or more processes

DFD construction will be initiated by identifying the major inputs and output to the system which have to be modeled and also major transformation. It will be identified along with the path from the inputs towards the output.

Flow chart VS DFD 

Flow chart emphasis: data flow diagram-> emphasis-> flow of data

The flow of control DFD- need not represent procedural information

Data dictionary

Whenever the flow model in terms of DFD is defined, there could be many named entities and relationships, etc. Names will be chosen which should be unique and they should convey precise meaning.

In the data dictionary we will find:

  1. List of names
  2. Structure of each data flow in the DFD
  3. Components in the structure of data flow
  4. Structure of the files which is shown in the DFD.


Data Dictionaries are used to manage mainly large software systems which are to be modeled. There will be many people involved at different levels name clashes can be resolved

It works as storage for maintaining organizational records systematically.

To conclude all names, types, attributes must be entered in the dictionary.

3. ER diagrams:

Entity-Relationship models are mostly used by database professionals to represent logical structures. They also are used as a tool for analyzing the software system. The initial table for the table will determine by converting the E-R model to the tables since each entity in an E-R diagram will represent the table and also a relationship that suggests different attribute fields in the table.

A logical database will be designed which will carry out with the E-R model which represents it using E-R diagrams.

E-R model is the high-level conceptual data which is developed by PPS Chen in the year 1976 which is used to represent real-world objects. It is called entities and the relationship.

These components will represent the overall logical structure of a given database application.

E-R diagram convention for the attribute types:

  1. Attributes will be displayed as ovals or eclipse with the attribute name which encloses in it which are connected to the relevant entity by the straight line.
  2. Entity name appears in upper case in a rectangle box whereas attribute name which is written in lower case in an oval.
  3. Derived attribute which is shown in the dotted line oval
  4. Multivalued attribute will be displayed in double line oval
  5. In case of composite attribute its components attributes which are displayed as ovals stems out from the composite attributes.


  1. What is DFD? Explain
  2. What are advantages of data dictionary?
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