Why Is A Data Dictionary Important In Structured Analysis

Introduction

The analyst should assure that each process, data flow and data store appearing in the logical DFD is defined in the data dictionary. The entries should contain sufficient detail so that other members of the project team can understand the definitions when they are needed.

What exactly is the meaning of Data Dictionary?

It is a catalogue of all elements in a system. It’s a document that collects, co-ordinates & confirms what a specific data terms mean to different people in the organization. The basic reference work for finding the attributes and names of data elements used throughout the system. These elements centre around data & they are structured to meet user requirements and organization needs. It is must that all data elements are included in the data dictionary. The major elements are data stores, processes &data flow. Data Dictionary stores descriptions & details of these elements.

Data Dictionary should be able to provide the following information:

How many characters are there in a data item (data element, field)?
By what names is it referenced in the system?
Where is it used in the system?

It is important to update the data dictionary as changes occur. The dictionary is developed during the Data Flow Analysis and assists the analysts involved in determining systems requirements, however its contents are used during systems design as well.

Why Important Data Dictionary is?

To manage the details

Both large and small systems have large quantities of data flowing through them. If Analysis try to remember it all, then chances are for important elements to be left out. The information of the data flow should be recorded.

Communicate Meaning

Data Dictionary assists in ensuring common meanings for system elements and activities. It records additional details about the data flow in a system so that all persons involved can quickly look up the descriptions of data flows, data stores and processes.

Document System Features

Documenting the features of an information system is the third reason for using Data Dictionary systems. Features include the components or parts and the characteristics that distinguish each. Why each process is performed and how often it is used, is documented.

Documenting system features produces more complete understanding. Once the features are articulated and recorded, all members of the project will have a common source for information about the system.

Facilitate Analysis

The major reason for Data Dictionary is to determine whether new features are needed in a system or whether changes of any type are in order.

Locate Errors and Omissions

The dictionary consists information of transactions, inquiries, capacity and data this tells us a great deal about the system and allows you to evaluate it. This information needs to be checked to ensure its completeness and accuracy. The dictionary is used to locate errors in the system description such as :

Conflicting data flow description
Processes, neither receive input nor generate output.
Data stores that are never updated.

These need to be corrected. In dictionaries the process of recording the information will usually reveals errors.

What does a data Dictionary record?

All parts of an information system such as transactions, reports, inquires, output files & databases depend upon data.

The dictionary contains two types of descriptions for data flowing through the system as:

Data elements
Data structures

Figure 1: Data Description hierarchy

Data Elements

Data elements form the most fundamental data level. They are grouped together to make up a data structure. Other names for data element are field, data item or elementary item. It is the smallest unit which has meaning. E.g, of data elements are employee name, grade, date of joining etc. These are grouped together to make up the employee register. They are building blocks for all other data in the system. By themselves they are meaningless to the user.

Data Structures

It is a set of data elements that are related to one another and that collectively describe a component in the system. E,g, of data structure : employee register, consists of data elements such as employee name, date of joining, exit code, exit date, dob, dept, grade and so on.

Data flows and data stores both are data structures. Another way of saying this is if data structures are moving, they are called data flows. When data structures are at rest and not moving they are called data stores. All data structures are defined in a dictionary entry. They consist of relevant elements that describe the entity or activity being studied. The employee register data structure consists of the following major components. The data structures are broken down into their lowest level data items. For example: employee name, date of joining, exit code, exit data, department, grade, basic salary, DA, HRA, Bank code, bank name, bank address, account no, monthly net salary earned.

Describing Data Flows

Data flows are data structures in motion. The contents of a data flow are expressed by defining the name of the data structure that pass along it.

It consists of:

The source of the data flow
The destination
The volumes of each data structure or transaction
The present physical implementation of data flow

Describing Data Stores

Data stores is a data structure at rest. The contents of each data store is described in terms of data structures found in it. And made up of the data flows that are input & those that are output from it. While describing the physical organization of the data store, the details of primary key, secondary key should be included.

Describing Processes

The logic of processes are documented in various ways such as decision tables, decision trees & structured english. The description of the logic of a process cannot be included in the data dictionary at all times.

What’s included in the data dictionary to describe a process is :

Inputs and outputs of the process
Logic is summarized
Reference to the place in the functional specification documentation where the logic is explained.

Describing Glossary Entries

In a number of applications, the user has his own jargon which the analyst or other team members may not be familiar with. The data dictionary is a convenient place to record these glossary items.

Summary

In a system data dictionary is a catalogue of all elements. The dictionary is developed during the Data Flow Analysis and assists the analysts involved in determining systems requirements. he dictionary consists of information of transactions, inquiries, capacity and data. Data Structures is a set of data elements that are related to one another & collectively describe a component in the system.