Information System Analysis
Topic 2
Data Gathering
 Observations

Observation usually means just that –watching and seeing

See firsthand the relationships that exist between decision makers and other
organizational members.

Types of data gathered this way cannot easily be collected by other techniques.

The key advantage of observation is firsthand information: You can take notes that
describe the activities as they occur.
 Questionnaires

Questionnaires are special-purpose documents that allow the analyst to collect
information and opinions from respondents.

Types of Questionnaires:1. Free-format questionnaires:Offer the respondent greater latitude in the answer.
2. Fixed-format questionnaires:Contain questions that require selection of predefined responses from
individuals.
Example:- Multiple-choice questions

Questionnaires Procedure:-
1. Determine what facts and opinions must be collected and from whom you should
get them.
2. Based on the needed facts and opinions, determine whether free or fixed-format
questions will produce the best answers.
3. Write the questions
4. Test the questions on a small sample of respondents.
5. Duplicate and distribute the questionnaires
 Interviews

Interviews are a fact-finding technique whereby the systems analysis collect
information from individuals through face-to-face interaction.
Types of Interviews : Unstructured interviews are conducted with only a general goal or subject in
mind and with few, if any, specific questions.
 In structured interviews the interviewer has a specific set of questions to ask of
the interviewee
Types of Interview Questions : Open-ended questions allow the interviewee to respond in any way that seems
appropriate.
 Closed-ended questions restrict answers to either specific choices or short direct
responses.
Procedure to conduct an Interview :1. Select interviewees.
2. Prepare for the Interview
3. Conduct the Interview
4. Follow up on the Interview
Interview Question Guidelines :1. Use clear and concise language.
2. Don’t include your opinion as part of the question.
3. Avoid long or complex questions.
4. Avoid threatening questions.
5. Don’t use “you” when you mean a group of people.
Process Modeling
 Process modeling involves graphically representing the processes, or actions,
that capture, manipulate, store, and distribute data between a system and its
environment and among components within a system.
Data Flow Diagram (DFD)
 It is a graphic that illustrates the movement of data between external entities
and the processes and data stores within a system.
 DFD can represent both physical and logical information systems.
 DFD are versatile diagramming tools. With only four symbols, represent data
flows, data stores, processes, and sources/sinks (External Entities)
DFD’s Symbols
External Entities
 Represent people or organizations outside of
the system being studied
Customer
 Shows the initial source and final recipient of data and information
 Should be named with a noun, describing that entity
External entities may be:
 A person, such as CUSTOMER or STUDENT.
 A company or organization, such as BANK or SUPPLIER.
 Another department within the company, such as ACCOUNT DEPARTMENT.
 Another system or subsystem, such as the INVENTORY CONTROL SYSTEM.
Processes
 It is the work or actions performed on data so that they are transformed, stored,
or distributed.
 Represent either:
–
A whole system, or A subsystem
–
Work being done, an activity
1
Add New
Customer
 Names should be in the form verb-adjective-noun
 Note:- when modeling the data processing of a system, it doesn’t matter
whether a process is performed manually or by a computer.
Data Store
 Name with a noun, may represent one of many different physical locations for
data. To understand data movement and handling in a system.
 Data stores are usually given a unique reference number, such as D1, D2, D3.
 Include any data stored, such as:
–
A computer file or database.
–
A set of tables .
–
A manual file of records.
D1
Customer
Master
Data flow
New Customer
 Data flow shows the data about a person, place, or thing that moves through the
system.
 Names should be a noun that describes the data moving through the system.
 Arrowhead indicates the flow direction.
Developing DFD
Use the following guidelines:
–
Make a list of activities and use it to determine (External Entities, Data Flows,
Process, Data Stores)
–
Create the context level diagram, including all external entities and the major
data flow to or from them.
–
Create Diagram 0 by analyzing the major activities within the context process.

Include the external entities and major data stores.
–
Create a child diagram for each complex process on Diagram 0 (Level 1).
–
Check for errors and make sure the labels you assign to each process and data
flow are meaningful.
Creating The Context Diagram
 It contains only one process, representing the entire system.
 The process is given the number zero.
 All external entities are shown on the context diagram as well as major data flow
to and from them.
 The diagram does not contain any data stores.
Creating Diagram 0
 Diagram 0 is the explosion of the context level diagram.
 It should include up to 7 or 9 processes.
–
Any more will result in a cluttered diagram.
 Processes are numbered with an integer.
 The major data stores and all external entities are included on Diagram 0.
Creating Child Diagram
 Each process on diagram zero may be exploded to create a child diagram.
 These diagrams found below Diagram 0 are given the same number as the
parent process.
–
Process 3 would explode to Diagram 3.
 Each process is numbered with the parent diagram number, and a unique child
diagram number.
 Examples are:
3.2 on Diagram 3, the child of process 3.
On Diagram 3, the processes would be numbered 3.1, 3.2, 3.3 and so on.
 External entities are usually not shown on the child diagrams below Diagram 0.
 If the parent process has data flow connecting to a data store, the child diagram
may include the data store as well.
 Each process on a lower-level diagram may be exploded to create another child
diagram.
 A lower-level diagram may contain data stores not shown on the parent process,
such as:
–
A file containing a table of information (such as a tax table).
DFD \ Rules
 Basic rules that apply to all DFDs:
–
Inputs to a process are always different than outputs
–
Objects always have a unique name

DFD
In order to keep the diagram uncluttered, you can repeat data
stores and data flows on a diagram
 Process
A. No process can have only outputs (a miracle)
B. No process can have only inputs (black hole)
C. A process has a verb phrase label
 Data Store
A. Data cannot be moved from one store to another
B. Data cannot move from an outside source to a data store
C. Data cannot move directly from a data store to sink
D. Data store has a noun phrase label
 Source/Sink
A. Data cannot move directly from a source to a sink
B. A source/sink has a noun phrase label
 Data Flow
A. A data flow has only one direction of flow between symbols
B. A fork means that exactly the same data go from a common location to
two or more processes, data stores, or sources/sinks
C. A join means that exactly the same data come from any two or more
different processes, data stores or sources/sinks to a common location
D. A data flow cannot go directly back to the same process it leaves
E. A data flow to a data store means update
F. A data flow from a data store means retrieve or use
G. A data flow has a noun phrase label
Data Dictionary
 This supplements the DFD by giving an organized listing of all data elements in
the system.
 It describes the meaning of the data flows and stores on the DFD.
 It describes the composition of aggregate packets of data moving along the flows
e.g. address might be described as house number, street, town, country etc.
 The data dictionary is a reference work of data about data (metadata)
 It collects, coordinates, and confirms what a specific data term means to
different people in the organization.
The data dictionary may be used for the following reasons:
– Provide documentation.
– Eliminate redundancy.
– Validate the data flow diagram.
– Provide a starting point for developing screens and reports.
– To develop the logic for DFD processes.
Data dictionaries contain:
–
Data flow.
–
Data structures.
–
Elements.
–
Data stores.
Data structures:
 Data structures are a group of smaller structures and elements.
 An algebraic notation is used to represent the data structure.
Data Dictionary \ Notation
 = Consist of
 + and
 ( ) “Parentheses” optional ( may or may not be present )
 { } “Braces” iteration ( repeated a number of times )
 [ ] “Brackets” (select one of several alternatives )
 ** a comment.
 @ identifier ( key field for a store )
 | (separates the choices in [ ])
Data Dictionary example
Customer Name =
First Name +
(Middle Initial) +
Last Name
Address =
Street +
(Apartment) +
City +
State +
Zip +
(Zip Expansion) +
(Country)
Telephone =
Area code +
Local number
Data Dictionary example
 name = title + first_name + ( middle_initial ) + last_name.
 title = [Mr|Mrs|Ms|Miss|Dr|Prof]
 first_name = { legal_characters }
 middle_initial = aplha_character.
 last_name = { legal_characters }
 legal_characters = [A-Z|a-z|’| |]
 alpha_character = [A-Z]
 name = * name for dispatch purposes *
Data Dictionary \ Example
Data Elements: Data elements should be defined with descriptive information, length and type
of data information, validation criteria, and default values.
 Each element should be defined once in the data dictionary.