Systems Analyst and Design - Data Dictionary

Data DictionarySystems Analysis and Design

Coquilla, Kimberly V.

The Data Dictionary

• Is a reference work of data about data (metadata), one that is compiled bythe systems analyst to guide them through the analysis and design.

• It is where the systems analyst goes to define or look up information aboutentities, attributes and relationships on the ERD (Entity RelationshipDesign).

Is the information you see in the data dictionary.

Importance of a Data Dictionary

• Avoid duplication

• Allows better communication between organizations who shares the same database.

• Makes maintenance straightforward

• It is valuable for their capacity to cross-referencing data items.

Enables one description of a data item to be stored and accessed by all

individuals so that definition for a data item is established and used.

Uses of Data Dictionary

• Validates the date flow diagram for completeness and accuracy

• Provides starting point for developing screen and reports.

• Determine the contents of data stored files

• Develop the logic for data flow diagram processes.

The Data Repository

• Repository – it is a larger collection of project information.

It contains the ff:

• Information about the data maintained by the system.

• Procedural logic

• Screen and report design

• Data relationships

• Project requirements and the final system deliverables.

• Project management information.

Sources of information

Data Dictionary

Data Flow

Data Stores

Data Processes

Data Processes

Data Flow

Data Stores

How data dictionaries relate to data flow diagrams ?

Four Categories of Data Dictionary

• Data Flows

• Data Structures

• Data Elements

• Data Stores

Defining the Data Flow

• Data flow is a collection of data elements

• It is the first component to be defined.

• Elements / Fields – used to describe details of each data flow.

• Data Structure – group of elements.

ID

Description

Source of the

Data Flow

Type of

Data Flow

Name of Data

Structure

Comments /

Notations

Destination of

the Data Flow

Volume per

unit of time

Name

Describing Data Structures

• Data structures and usually described using algebraic notations.

• An equal sign = means “is composed of”.

• A plus sign + means “and”.

• Braces { } indicates repetitive elements also called repeating groups or tables.

• Brackets [ ] represent an either/or situation.

• Parentheses ( ) represent an optional element.

• Each structural record must be further defined until the entire set is broken down into its component elements.

How are the symbols used ?

Repeating items

Optional element

“and”

“is composed of ”

“either/or” situation

Groups of elements /

Structural Records

Logical and Physical Data Structures

• Logical Data Structure – shows what data the business needs for its day-to-day operations. Ex. Name, Address, Orders.

• Physical Data Structure – includes additional elements necessary for implementing the system.

Examples of physical design elements:

• Key fields used to locate records.

• Codes to identify the status of master records.

• Transaction codes

• Repeating group entries containing a count of how many items are in the group.

• Limits on the number of items in a repeated group.

• A password

Other examples:

•12{Monthly Sales} – indicates 12

months in a year.

•Customer Master File = {Customer

Records} – means indefinitely.

• 51{Order Line} – both means as a

structural record and a repeating item

based on Figure.

Data Elements

• Data elements definitions describe a data type.

• Each element should also be defined to indicate specifically what it represents. It should be specific.

ID

Description

Name

Aliases

Default Value

Comment /

Remarks

Length of the

ElementData Type

Base / Derive

Validation

Criteria

Inputs and

Outputs

ID

Description

Name

Aliases

Default Value

Comment /

Remarks

Length of the

ElementData Type

Base / Derive

Validation

Criteria

Data Stores

• Data Stores are created for each different data entity being stored.

ID

Description

Name

Aliases

Max., Ave., & Growth

of Records

Date Set Name

File Format

File Type

Data Structure

Primary & Secondary

Keys

Comments

Creating the Data Dictionary

Parent

Processes

Data

Dic

tion

ary

Data

Flo

w D

iag

ram

Child Diagram

Analyzing Input and Outputan important step in creating the data dictionary is to identify and

categorize system input and output data flow.

Different fields for Input and

Output Analysis:

1. Descriptive Name

2. User Contact

3. File Type (is it an Input or Output?)

4. File Format

5. Sequencing Elements

6. List of Elements

7. Comments

Developing Data Stores

Data flows represent data in motion data stores represent at restData stores contain information of a permanent or semi permanent nature.When data stores are created for only one report screen we refer them as “user views”

Conclusions

The ideal data dictionary is automated, interactive, online andevolutionary.

The data dictionary should be tied into a number of systems programs sothat when an item is updated or deleted from the data dictionary, it isautomatically updated or deleted from the data base.

The data dictionary may also be used to create screens, reports andforms.

-Fin.-