is 320 notes for chapter 8

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IS 320 Notes for Chapter 8

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IS 320 Notes for Chapter 8. ClassX Problems: Low-Tech Fix. Use last year's videos on ClassX Select "Semesters" tab Select IS 320 Select the week/lecture of interest. Data Dictionary. This week's topic is not difficult for IS/CS students, so we won't spend class time on it - PowerPoint PPT Presentation

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IS 320Notes for Chapter 8

ClassX Problems: Low-Tech Fix

• Use last year's videos on ClassX Select "Semesters" tab Select IS 320 Select the week/lecture of interest

Data Dictionary

• This week's topic is not difficult for IS/CS students, so we won't spend class time on it The remainder of the slides have notes

Process vs. Data Centricity

Data-Centric Approach Process-Centric Approach

 

What data does the system need?

 

 

What is the system supposed to do?

Tends to have an enduring design stability due to low volatility in organizational data needs.

 Design stability is necessarily limited due to constant changes in business processes.

  

The file structure is enterprise dependent.

 

 

The file structure is application dependent.

 

Data redundancy is generally limited and controlled.

 

 

Data redundancy is generally massive and uncontrolled.

Data DictionaryWhat does “Backordered item” mean?

What does “New Customer info.” contain?

How does the “account receivable report” look like?

Data Dictionary

A list of names/identifiers used in the system models arranged alphabetically; they include their meaning and information about them

Types of information provided:Description of dataIf composite data, describe elementsData representation or typeCreator, creation date, user contactsOther names for the data (aliases)

Data Dictionary

Data dictionary is a metadata

Created in parallel with DFD

Created in top-down approach

Data dictionary should be kept up-to-date with the DFD model

Data DictionaryAdvantages:

Documentation for the whole system

Eliminate redundancy in a system which has been created by different people

Identify aliases

Provide a starting point to develop reports and screens

Validates the data flow diagrams for completeness and accuracy

Develop the logic for DFD processes

Data Dictionary Contents

Data dictionaries contain:Data flow.

Data structures.

Elements.

Data stores.

Process

Data Flow Description

ID numberName (as it appears in DFD)DescriptionSourceDestinationType (file, screen, report, form, internal)Data structure nameHow frequently producedComments

Defining Data Flow (Continued)

The source of the data flowThis could be an external entity, a process, or a

data flow coming from a data store.

The destination of the data flow

Type of data flow, either: A record entering or leaving a file.

A report, form, or screen.

Internal - used between processes.

Defining Data Flow (Continued)

The name of the data structure or elements

The volume per unit timeThis could be records per day or any other unit of

time.

An area for further comments and notations about the data flow

Data Store

ID numberNameAlias nameDescriptionType (manual, computerized)File format (database, sequential, Indexed)Maximum/ average number of recording

This helps the analyst to predict the amount of disk space required.

File nameData structure

Data Structure

For compositional data flow and data store elements

Describe the elements of the data structure using algebraic notation

= Composed of

{ } Repetition

( ) Optional

+ and

[ / ] or

Data StructureExample:

Student record= student ID + Student name+

Address +

Date of birth +

Gender +

Nationality +

Telephone number +

(mobile telephone number) +

{ course record}

Data Elements

Each element in the data structure should be describedID numberNameAliasDescriptionType (Base: entered from user, derived: computed)

Length (in characters) [max or fixed]Data type (date, numeric, alphanumeric)Input/Output formatValidation criteriaDefault valueComments

Defining Elements

Aliases, which are synonyms or other names for the element

These are names used by different users within different systems

Example, a Customer Number may be called a: Receivable Account Number.

Client Number.

Defining Elements

A base element is one that has been initially keyed into the system.Input from an external entity in the DFD

A derived element is one that is created by a process, usually as the result of a calculation or some logic.Output from a process in the DFD

Data Store Definition

If the file is computerized, the file format designates whether the file is a database file or the format of a traditional flat file.

The maximum and average number of records on the file

The growth per yearThis helps the analyst to predict the amount of disk space

required.

Data Store Definition

The data set name specifies the table or file name, if known.In the initial design stages, this may be left blank.

The data structure should use a name found in the data dictionary.

Logical and Physical data

Logical data structures is what the user sees

Physical data structure is what the software needs for processing (e.g. flags, key fields for search, ..)

Using the Data Dictionary

Data dictionaries may be used to:Create reports, screens, and forms.

Generate computer program source code.

Analyze the system design for completion and to detect design flaws.

Creating Reports, Screens, Forms

To create screens, reports, and forms:Use the element definitions to create fields.

Arrange the fields in an aesthetically pleasing screen, form, or report, using design guidelines and common sense.

Repeating groups become columns.

Structural records are grouped together on the screen, report, or form.

Data Dictionary Analysis

The data dictionary may be used in conjunction with the data flow diagram to analyze the design, detecting flaws and areas that need clarification.

Data Dictionary Analysis (Continued)

Some considerations for analysis are:All base elements on an output data flow must be

present on an input data flow to the process producing the output.

Base elements are keyed and should never be created by a process.

Data Dictionary Analysis (Continued)

A derived element should be output from at least one process that it is not input into.

The elements that are present on a data flow into or coming from a data store must be contained within the data store.

Process Data Process numberProcess nameDescriptionInputOutputType (batch, online, manual)Prewritten code: ready made functional librariesProcess logic (Business rules)Reference to description tables or structuresUnresolved issues: (notes to check with users)

Process Specifications

Process specifications are created for primitive processes on a data flow diagram.

They are also called minispecs.

AdvantagesUnderstand how the process works and go back to users if not

clear

Describe what should happen for designer and programmer

Validate the DFD

Structured English

based on structured logic and Simple English statementsAppropriate technique for analyzing the system when

structured decisions are not complex.Express all logic in terms of sequential structures, decision

structures, case structures, or iterations.Use and capitalize accepted keywords such as IF, THEN, ELSE,

DO, and PERFORM.Indent blocks of statements to show their hierarchy.Underline words that have been described in the data dictionary

Describing Processes

Example: Bonus monthly payment (Structured English)

For each customer

Read Customer record

For each item rented between 1/10 to 1/11

add total

End for

If total is greater than or equal to 50$ then

send bonus and thank you letter

End if

End for

Automatic Data Dictionary

Using CASE tools:Easy to change and add

Created and integrated with other models

Checks that the DFD is valid e.g. all data needed for a process is input to it

Data store contains data input/ output to/from it

Derived data should be output from process

Checks data source and destination in DFD

Use data structures to create reports and screens

Exampleshttp://federalstudentaid.ed.gov/static/gw/docs/ciolibrary/ECONOPS_Docs/EDM-

EnterpriseDataDictionaryStandards.pdf

http://www.pnamp.org/sites/default/files/best_practices_for_data_dictionary_definitions_and_usage_version_1.1_2006-11-14.pdf

http://www.cidr.jhmi.edu/requirements/GWAS_Data_Dictionary.pdf

Guest Speaker

• We often need to think "outside the box" as systems analysts

• Vint Cerf on "Reinventing the Internet"

http://www.youtube.com/watch?v=qguED5Aouv4