Section 08 Data Dictionary - Structures & Elements

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08 THE DATA DICTIONARYStructures & Elements

And Franchise Colleges

By MANSHA NAWAZ

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Introduction

• We've seen how to build up a useful model of a system using DFDs.

• The technique of explosion within DFDs is a powerful way of breaking a complex problem down into a number of simpler problems.

• However, we still haven't reached the level of detail that would be needed by a developer to actually build the system.

• This is provided by the Data Dictionary.• A Data Dictionary is a collection of further details about

everything on a set of DFDs, not only about data, but also about processes.

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Recording Data in the Data Dictionary• The data parts of DFDs are data flows and data stores.

• On the DFD we have just a name for these, so we need to record the content and structure of these before we can develop software.

• For our logical model, we want a way of describing the data that will accommodate any physical implementation.

• This is done by describing the data in terms of data elements and data structures.

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The Data Dictionary

• it is a receptacle for storing information on all system items– data stores– data flows– processes– external entities

• it contains a logical description

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– Data Dictionary• Data Stores and Flow lecture 08

– Structures & Elements

• Data Stores and Flow – Usage

lecture 09

• Process Descriptions – Mini Specs and Sample Screen Shots lecture 10

– NORMALISATION lecture 11

• Database Tables derived from Data Store Descriptions

Document : Design Specification

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• THE DATA DICTIONARY

• : Data Structure & Elements

SYSTEMS DESIGN

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• Aim– to be able to describe data in terms of its

constituent structures and elements

• Objectives– to identify indivisible data items– to record elements using a given syntax– to identify collections of data items– to record structures using a given syntax

Learning Aims

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• the need to describe data

• a data hierarchy

• data elements

• data structures

• Yourdon’s data notation

Lecture Outline

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• the DFD gives a logical view of a system’s functionality

• a DFD provides use with DATA STORES & DATA FLOWS

• the designers/programmers will need to know the logical composition of the data

• what it is and not the actual values

Describing Data

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• Each DATA STORE requires a data description comprising of its Data Structures & elements

• Each DATA FLOW may requires a data description comprising of its Data Structures & elements(only record for dataflow whose data description is different from its

datastore)

Starting Point:

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• data seen as a two level hierarchy

• data elements– smallest logical item

• data structures– collection of elements– collection of structures– collection of both

Data Structure

Data Element

A Data Hierarchy

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• the items of data within the problem domain that can’t be further divided

• for example an address– 15 High St, M’boro, Cleveland , TS4 5KL

• this can be broken down into elements– a house number, a road, a town, a county and

a postcode

• each of these can’t be further divided

Data Elements

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• the items of data that can be further sub-divided

• the data item ‘address’ is a structure because it can be further divided into meaningful data items

• here the structure consists of a number of elements but it is possible to have structures nested within structures

Data Structures

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• Structures:ADDRESS = houseno + road + town +

county + postcode

• Elements:houseno = 1{char}3 **usually numeric

road = 1{char}15

town = 1{char}10

county = 1{char}10

postcode = 6{char}7 ** format $$# #$$ where each $ = [A..Z] each # =

[0..9]often the elements are described using the types found

in databases - char, integer, real, boolean, date

Example

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X = Y X is composed of Y

X + Y X and Y

(X) X is optional item

j{X}k iterated item, j/k low/upper limit

[X | Y] item to be selected from X or Y

@X identifier item

** comment

Yourdon’s Notation

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• this division of data in elements and structures allows analysts to re-use defined items

• other structures can have the structure ADDRESS as a constituent part but the elements that make up ADDRESS and ADDRESS itself need only be defined once

Avoid Redundancy

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Recording Elements & Structures

• check each data item in the system – identify all elements & structures

• create a list of each type and record– name

• elements lower , STRUCTURES upper case

– description• one sentence english text

– composition • use given notation

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Contd.– aliases

• other names used, delivery note/despatch note

– discrete values or continuous range limits• NZ = New Zealand or 100-1000

– default value• preset value on creation

– validation information• if title = Mr then sex = Male

– related data items• houseno, associated with structure ADDRESS

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– Data Dictionary lecture 08

• Data Stores - Structures & Elements lecture 08

– Start by listing each DATA STORES– For each data store list structures and elements– Draft a form view for the data store

• Data Flow - Structures & Elements lecture 08

– Start by listing each DATA FLOW– Copy and paste the related data store structures and elements– Cut or delete the structures and elements which are not required– Draft a form view for the data flow.

• Data Stores and Flow Usage lecture 09

• Process Descriptions lecture 10

Document : Data Dictionary

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Please Note:

• Ascent allows you to record the Data Dictionary Structures and Elements and a guide has been produced DD in Ascent.

• Unfortunately Ascent is weak when

producing data dictionary content for a report. So feel free to utilize MS Word when creating your Data Dictionary Structures and Elements.

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Summary• For each Data Store• describe logical data• data elements• data structures• notation• minimal redundancy

Self Study• review the lecture• complete exercises

from the course workbook

•

Summary & Self Study

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Further Reading

• Notes from Annette Marshall

• http://outranet.scm.tees.ac.uk/users/u0018257/SDV/SDevWk5.doc