Data Dictionary Systems Analysis and Design Coquilla, Kimberly V.
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.-