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Transcript of 1 INFORMATION SYSTEMS Rafiqul Islam Software Project Manager eDicte Tech Solutions.
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INFORMATION SYSTEMS
Rafiqul IslamSoftware Project Manager
eDicte Tech Solutions
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Module-1
INFORMATION SYSTEMS – AN INTRODUCTION
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INFORMATION SYSTEMS
A definition of information systems is: Interrelated components working together to collect, process, store, and disseminate information to support decision-making, coordination, control, analysis, and visualization in an organization.
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DATA AND INFORMATION
DATA Raw material of information. Groups of nonrandom symbols that
represent quantities, actions, objects, etc. in the from of text, image, or voice.
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DATA AND INFORMATION
INFORMATION Processed data in meaningful form to the
recipient Of real or perceived value in the current
or prospective actions and decisions Having reusable resources A surprise or news value that reduces
uncertainty
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PHYSICAL SYSTEMS AND IS
Example: Inventory Monitoring System Information system: Flow of data such as
material requests, purchase requests, material delivery advices, and so on.
Physical system: Actual flow of materials from the stores to the production shops or from the suppliers to the stores.
Associated will be the materials handling systems that need to be optimized.
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PHYSICAL AND INFO. FLOWS
Information Flow
Supply Chain
Raw Materials
Finished Goods
Material
Manpower EquipmentMoney
Physical Flow
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FEEDBACK AND INFO. FLOWS
Info. Flow
Information Flow
ProcessInput Output
Physical Flow
Desired Output
Control Signal
Information Flow
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FEEDBACK AND INFO. FLOWS• Negative feedback loop control gives a
new idea about the definition of information.
• Information can be defined as a control signal or an error signal that can help make vital decisions about controlling the inputs of a physical system.
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CATEGORIES OF INFO. SYSTEMS
• Application software :: classical management information systems
• Real time software :: missile defense systems • Systems software :: operating systems • Embedded software :: radar navigation
packages • Communications software :: telephone
switching systems • Process control software :: refinery drivers.
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APPLICATION SOFTWARECriteria Non-Application
SoftwareApplication Software
Data Less Data Huge Data
Input Less input - usually organized
Huge input. Need effort to i) Collect ii) Organize iii) Maintain steady flow
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APPLICATION SOFTWARECriteria Non-Application
SoftwareApplication Software
Processing
High Processing of Data
Although less per record but it is high for all records
Algorithms
Large Number of Algorithms with high complexity
Less Number of Algorithms with less complexity
Output Less output - easy to organize
Huge output. Need effort to Organize and Disseminate
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APPLICATION SOFTWARE• Strong customer focus.
• Understand customer requirements
• Implement appropriate solution to integrate the business processes of the customer.
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APPLICATION SOFTWARECOMPLEXITIES OF DATA
Complexities of input data need be resolved
right at the requirements analysis stage. Many a time, analysts tends to underestimate
the complexities of a system The result is often a poorly designed software
Later, during implementation, the customer
brings in the complexities one after another and the software need to be redeveloped.
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CASE STUDYA SIMPLE INTEREST FORMULA IS ALL WE
NEED HERE!
When PQR industrial development corporation invited ABC consultants for developing a software for tracking its term loans - it all seemed too easy to the system analyst - Rohit Sarawagi.
Rohit, a fresh MBA from IIT Kharagpur, spent a few hours time with Mr. Patil, GM, Term Loans. "All we need here is a simple interest formula!" - exclaimed Rohit to his colleagues during a tea-time discussion.
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CASE STUDYTerm Loans are usually offered by PQR to
aspiring industrialists who need to pay back the loan in a number of instalments.
Schedules are usually prepared for the payment of the principal amount as well as the interests.
PQR wants ABC to develop a software for easy tracking of the term loans sanctioned to the borrowers.
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CASE STUDYAtul Pradhan, a colleague of Rohit, was not too
amused. He pointed out to Rohit that it is not always that the borrowers of Term Loans pay back in time.
PQR has to then charge interests on interests, known as penal interests, in addition to the normal payment charges.
And do they pay the penal interests on time? - Usually not, says Atul, the borrowers often ask for rescheduling of payments - often falter the new schedule as well, and invariably ask for rescheduling of the reschedule!
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CASE STUDYWhen Rohit met Mr. Patil the next day, Mr
Patil said - did I mention you about the court cases yesterday?
What about court cases? Oh, some naughty borrowers move to court
challenging the amount to be paid. Then we have a figure to be paid according to us, a figure as per them, and possibly a third figure negotiated by the court!
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CASE STUDYAnd do we have the rescheduling of the
negotiated payment figure of the rescheduled penal interest as well?
Why not? We may as well negotiate that in the court!
A SIMPLE INTEREST FORMULA IS ALL WE NEED HERE!
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Module-2
INFORMATION SYSTEMCLASSIFICATIONS
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STRUCTURE OF INFORMATION SYSTEMS
Based on Operating ElementsPhysical Components:
• Hardware• Software• Database• Procedures• Operating Personnel
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STRUCTURE OF INFORMATION SYSTEMS
Based on Operating ElementsProcessing Functions:
• process transactions• maintain master files• produce reports• process inquiries• interactive support
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STRUCTURE OF INFORMATION SYSTEMS
Based on Operating ElementsOutputs for users:
• transaction documents• preplanned reports• preplanned inquiry responses• ad-hoc reports• ad-hoc inquiries• user-machine dialogue results.
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STRUCTURE OF INFORMATION SYSTEMS
Based on Decision Support
• Structured Programmable Decisions• Unstructured un-programmable decisions
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STRUCTURE OF INFORMATION SYSTEMS
Based on Management Hierarchy
Level of Management
Function
Top/Senior Management
Long-range decisions Strategic Planning
Middle level Management
Carrying out plans and goals specified by the top management,
Management Control and Tactical Planning
Knowledge Management
Knowledge work Data work
Operational Management
Monitoring day-to-day activities
Operational Planning and Control
Transaction Processing
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STRUCTURE OF INFORMATION SYSTEMS Based on Organizational Functions Sales and Marketing Manufacturing Finance Accounting Human Resources Logistics Information Processing
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MIS TRIANGLE
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TPS: TRANSACTION PROCESSING SYSTEM
A computerized system that performs and records the daily routine transactions in the conduct of a business.Information Inputs: Transactions, EventsProcessing: Sorting, Listing, Merging, UpdatingInformation Outputs: Detailed Reports, Lists, SummariesUsers: Operations Personnel, Supervisors
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TPS: TRANSACTION PROCESSING SYSTEM
Examples
Order Tracking and Processing, Machine Control
Cash Management, Payroll, Account Payable
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OAS: OFFICE AUTOMATION SYSTEM
OAS serves the information needs at the knowledge level of an organization to aid data workers.
Information Inputs: Documents, Schedules Processing: Documents, Management,
Scheduling, Communication
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OAS: OFFICE AUTOMATION SYSTEM
Information Outputs: Documents, Schedules,
Mails Users: Clerical Workers
Examples Word Processing, Image Storage, E-
Calendars
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KWS: KNOWLEDGE WORK SYSTEM
KWS serves the information needs at the knowledge level of an organization to aid knowledge workers.
Information Inputs: Design Specifications, Knowledge Base
Processing: Modeling, Simulation
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KWS: KNOWLEDGE WORK SYSTEM
Users: Professionals, Technical Staff Examples
Knowledge Work Analysis, Engineering Workstations
Graphic Workstations, Managerial Workstations
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MIS: MANAGEMENT INFORMATION SYSTEM
MIS primarily serves planning, controlling, and decision-making at the management level.
Characteristics of MIS Reporting and Control Oriented Rely on existing corporate data and data flows Have little analytical capability Aid decision-making using past and present data
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MIS: MANAGEMENT INFORMATION SYSTEM
Characteristics of MIS (continued) Relatively inflexible Internal rather than external orientation Information requirements are known and stable Development time is usually one to two years.
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MIS: MANAGEMENT INFORMATION SYSTEM
Information Inputs: Summary Transaction Data, High Volume Data, Simple Models
Processing: Routine Reports, Simple Models, Low Level Analysis
Information Outputs: Summary and Exception Reports
Users: Middle-level Managers
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MIS: MANAGEMENT INFORMATION SYSTEM
Examples
Sales Management, Inventory Control Annual Budgeting, Capital Investment
Analysis Relocation Analysis
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DSS: DECISION SUPPORT SYSTEM
DSS supports decision-making of the management level of an organization.
DSS Characteristics Incorporate both data and models Assist in decision processes that are semi-
structured, unique, or rapidly changing. Support, not replace, managerial judgement Improve the effectiveness and not
efficiency of making decisions.
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DSS: DECISION SUPPORT SYSTEM
Information Inputs: Low Volume Data, Analytical Models
Processing: Interactive, Simulation, Analysis
Information Outputs: Special Reports, Decision Analysis, Responses to Queries
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DSS: DECISION SUPPORT SYSTEM
Users: Professionals, Staff Managers Examples
Sales Region Analysis, Production Scheduling
Cost Analysis, Pricing and Profitability Analysis
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ESS: EXECUTIVE SUPPORT SYSTEM
ESS serves senior managers of an organization for the support of strategy level decision-making.
Information Inputs: External and Internal Aggregate Data
Processing: Graphics, Simulation, Interactive
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ESS: EXECUTIVE SUPPORT SYSTEM
Information Outputs: Projections, Responses to Queries
Users: Top/Senior Managers Examples
Sales Trend Forecasting, Operating Plan
Budget Forecasting, Profit Planning
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Module-3
INFORMATION SYSTEMS FOR COMPETITIVE
ADVANTAGE
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USING INFO SYSTEMS FOR COMPETITIVE ADVANTAGE
THEFIRM
TraditionalCompetitors
NewMarketEntrants
Suppliers Customers
SubstituteProducts /Services
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BASIC STRATEGIES IN COMPETITIVE FORCES MODEL
Product Differentiation: Creating unique new products and services that can be easily distinguished
Focused Differentiation: Creating new market niches by identifying a specific target for a product/service
Developing tight linkages to customers and suppliers: Creating ties with customers and suppliers to “lock” customers and tie suppliers
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BASIC STRATEGIES IN COMPETITIVE FORCES MODEL
Becoming the low cost producer: Producing goods and services at a lower price than competitors without sacrificing quality and level of service.
• Information systems can make them competitive
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LINKING WITH CUSTOMERS & SUPPLIERS
1. Prevailing Delivering Practice at Hospitals
Suppliers Inventory Delivery Hospital Hospital(Bulk Storage) System Storeroom Wards
2. Just-in-Time Supply Method
Suppliers Inventory More frequent Hospital Hospital(Bulk Storage) Deliveries Storeroom Wards
3. Stockless Supply Method
Suppliers Inventory Daily Deliveries Directly Hospital(Bulk Storage) to the Hospital Wards Wards
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ORGANIZATIONS AND INFORMATION TECHNOLOGY
Organizations InformationTechnology
Mediating Factors Environment Culture Structure Standard Procedures Politics Management
Decisions Chance
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MANAGEMENT, IT AND ORGANIZATION
BUSINESSSOLUTIONS
MANAGE-MENT
INFORMA-TIONTECHNOLOGY
BUSINESSCHALLENGES
INFORMATIONSYSTEM
ORGANIZA-TION
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CHALLENGES OF INFORMATION SYSTEMS
The strategic business challenge: How can businesses use information technology to design competitive and effective organizations?
The globalization challenge: How can firms understand the business and system requirements of a global economic environment?
The information architecture challenge: How can organizations develop an information architecture that supports their business goals?
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CHALLENGES OF INFORMATION SYSTEMS
The information system investment challenge: How can organizations determine the business
value of information systems?
The responsibility and control challenge: How can organizations design systems that
people can control and understand? How can organizations ensure that the
information systems are used ethically and in a socially responsible manner?
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ORGANIZATIONS AND INFORMATION TECHNOLOGY
Organizations InformationTechnology
Mediating Factors Environment Culture Structure Standard Procedures Politics Management
Decisions Chance
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MANAGEMENT, IT AND ORGANIZATION
BUSINESSSOLUTIONS
MANAGE-MENT
INFORMA-TIONTECHNOLOGY
BUSINESSCHALLENGES
INFORMATIONSYSTEM
ORGANIZA-TION
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CHALLENGES OF INFORMATION SYSTEMS
The strategic business challenge: How can businesses use information technology to design competitive and effective organizations?
The globalization challenge: How can firms understand the business and system requirements of a global economic environment?
The information architecture challenge: How can organizations develop an information architecture that supports their business goals?
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CHALLENGES OF INFORMATION SYSTEMS
The information system investment challenge: How can organizations determine the business value of
information systems?
The responsibility and control challenge: How can organizations design systems that people can
control and understand? How can organizations ensure that the information systems
are used ethically and in a socially responsible manner?
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Module-4
CONCEPT OFINFORMATION
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CONCEPT OF INFORMATION
Information • Information is data that has been
processed into a form that is meaningful to the recipient and is of real or perceived value in current or prospective actions/decisions.
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CHARACTERISTICS OF INFORMATION
• It is Reusable• Does not lose value over time• May give value by addition of credibility
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DIMENSIONS IN THE USE OF INFORMATION
• Information Presentation• Information Transmission• Information Interpretation• Information Use
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TRANSMISSION OF INFORMATION
Source Transmitter Encoder
Channel Receiver Decoder
Destination
Noise and Distortion
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INFORMATION INTERPRETATION
• Information Reduces Uncertainty • Even partial information may assist in
understanding. • Information has a ‘surprise’ or ‘news’ value.
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INFORMATION REDUCES UNCERTAINTY
Example: • In an interview, there are 10 equally likely
possible candidates. So, Information content of positively identifying the best candidate is:
• I = log210 = 3.32.• A message comes that only 4 candidates have
cleared the preliminary round.
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INFORMATION REDUCES UNCERTAINTY
• So, New Information content: • I = log24 = 2.0.
• Thus, Information value of the partial information (message):
• 3.32 – 2.0 = 1.32.
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REDUNDANCY IN INFORMATION
• Sometimes redundancy is very useful in information transmission.
• Example:• This cla** is held at SOM Build**g at 13.0*
ho**s.
• It is not necessary to decode every letter of the message.
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REDUNDANCY IN INFORMATION
• Human eyes are so much accustomed to observing redundancy in information, that sometimes Redundancy may be misleading:
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REDUNDANCY IN INFORMATION
• Often, we may read the above as INDIA, but in reality, it may be just this!!
•
• Hence, One should be careful about possible introduction of errors!
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INFORMATION PRESENTATION
• Interpretation of received messages are subject to misinterpretation /misunderstanding.
• The capacity of human to process information is limited (Information Overload).
• Methods to increase the sending/receiving efficiency of a system are needed.
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CASE STUDY:: E-BUSINESS AT DOMINO
• DOMINO as in Domino's Pizza• A worldwide enterprise with 5,600 stores and 18
distribution and supply centers, • Domino's relies on its 1,200 independent franchise
chain learned how to deliver timely information as well.
• Objective: Getting information to the right people in the right order.
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E-BUSINESS AT DOMINO• Domino's relies on its franchisees all over the
world to carry the company's commitment through to customers.
• A small headquarters staff in Ann Arbor, Michigan, manages the performance of each franchise directly, through travelling consultants and through field managers.
• Delays in reporting procedures led to franchise owners getting conflicting information from different sources, which in turn was upsetting the pizza chain's strict quality control efforts.
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E-BUSINESS AT DOMINO• The company needed a solution that would let
mobile managers document their plans with franchisees and simultaneously share the results with headquarters.
• Opportunity: Domino's knew the solution was to go online.
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E-BUSINESS AT DOMINO• A customized groupware application could eliminate
duplication of efforts and keep networked users informed.• A global intranet would provide an opportunity to
automate critical business processes, like financial reporting.
• Franchise managers could upload their performance information to Domino's central server and view how they rank against the worldwide operations.
• Challenges: Serving timely information to a thousand hungry clients.
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E-BUSINESS AT DOMINO• Ultimately, Domino's intranet would give 1,000
employees access to more than 50 applications and over 2,000 Web pages.
• The company needed a system easy to set up and maintain, yet scalable to add functionality as new applications and users came online.
• Domino's needed a system with security features to control exactly what information could be viewed by whom.
• The need was immediate – no time to look for the perfect solution for years together.
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E-BUSINESS AT DOMINO• Adding ingredients one at a time, Domino's chose
a spreadsheet-based groupware application with a Web server.
• The company phone directory and newsletter were the first to go online, while its core application, Contact Log, was being adapted from off-the-shelf sales force automation software.
• Contact Log tracks interactions between field consultants and owners, and stores associated documents. It is supported by interactive product information database.
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E-BUSINESS AT DOMINO• The second phase of Domino's intranet
development includes an online financial reporting system, linking directly to the company's data warehouse.
• Domino's Pizza envisions dozens of future phases, which will continue to add more mission critical applications to the intranet.
• • Results: Any way you slice it, Domino's is saving
time and money.
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E-BUSINESS AT DOMINO• Domino's applications allow employees to check
calendars, view policies, and download mission critical information.
• The system contains a detailed document library for an easy access to a broad range of company information, such as corporate accounting procedures and calendar.
• The most popular application on the intranet is an online discussion forum that covers topics from product distribution issues to human resources management.
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INFORMATION INTERPRETATION
• Information Reduces Uncertainty
• Even partial information may assist in understanding.
• Information has a ‘surprise’ or ‘news’ value.
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INFORMATION PRESENTATION
Discretion on Info. Content & Distribution• Objective: Avoid undesirable effects & reduce
workloads.• Message Delay: Avoid overload.• Message Filtering or modification: Modify by
summarization, and Block certain data by filtering.
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DISCRETIONS ON INFO. CONTENT & DISTRIBUTION
• Uncertainty bias: Reduce data transmission. Remove recipient from the contact of detailed data.
• Presentation Bias: Bias by order and grouping. Bias by selection of the limits, Bias by the selection of the Graphic layout (Choice of Scale/Graphics/Size/Color).
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PRESENTATION BIAS• Order and Grouping: Presentation Bias can be
introduced by a suitable choice of order and grouping, such as Alphabetic Order, Order by rate of return, Order by rate of return within industry.
• Choice of limits: Use of too low or too wide limits can bias the viewer.
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PRESENTATION BIAS• Choice of Graphics: • Choice of Scale: to affect the perception of
differences in trend charts.• Choice of Graphic: Visual difference comparison
is difficult with trend charts, relatively easy with superimposed lines, and in-between for bar charts.
• Choice of Size: to minimize differences• Choice of Color: Red to draw attention
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QUALITY OF INFORMATION• Information may be presented and transmitted
efficiently and interpreted correctly, but it may not be used effectively.
• Quality of information is determined by how it motivates human action and contributes to effective decision-making.
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DECISION-MAKER PERCEPTION
Decision-maker Perception for Quality of Information
• Utility of Information• Information Satisfaction• Error and Bias
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UTILITY OF INFORMATION• Form utility• Time Utility• Place Utility (Physical Accessibility)• Possession Utility (Organization Location)
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COST & VALUE OF INFORMATION
• Information has a cost and a value• One can increase value by increasing accuracy and
utility• One can reduce cost by decreasing accuracy and
utility
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INFORMATION SATISFACTION
• Contribution of a particular item of information is difficult to find in the context of improvement in decision-making.
• So measure the degree of satisfaction of the decision-maker with the output of the information system.
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ERROR AND BIAS• High quality rather that quantity of information is
needed• Error and Bias reduce the quality• Bias is caused by the ability of the individuals to
exercise discretion in information presentation• Detected bias can be adjusted• Errors cannot be adjusted by the
decision maker.
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ERROR CAUSES• Incorrect Data measurement and collection• Wrong processing procedures• Less or non processing of data• Wrong recording/correcting• Incorrect master file• Mistakes in procedure• Deliberate Falsification
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AVOIDING ERRORS
• Internal control• Internal/External Auditing• Addition of confidence limits• User instructions in measuring or processing of
data
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BIAS• Handled by procedures to detect and measure it
and to adjust for it.• Bias in Information may occur in:
• Data Acquisition• Processing of Information• Related to Output• Related to Feedback
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BIASES RELATED TO DATA ACQUISITION
• Availability Bias: Frequency of well-publicized events are usually overestimated.
• Selective Perception: Own experience bias – what one expected to see. People usually downplay or disregard conflicting evidence.
• Frequency Bias: Absolute number of successes are more important than their relative number.
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BIASES RELATED TO DATA ACQUISITION
• Concrete Information Bias: People rely more on concrete Information rather than on statistical.
• Illusory correlation: People usually choose inappropriate variables for prediction.
• Data Presentation Bias: Order effects/ mode of presentation /mixture of qualitative and quantitative/logical data display.
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INFORMATION PROCESSING BIASES
• Inconsistency: People are sometimes inconsistent in their processing of information.
• Conservation: Decision-makers are often conservative.
• Non-linear extrapolation: Decision-makers are unable to visualize exponential growth/decay (which may be non-linear and dramatic!)
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INFORMATION PROCESSING BIASES
Heuristics to reduce mental efforts: • Rule of thumb• Anchoring and adjustment• Representativeness• Law of small numbers• Justifiability
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INFORMATION PROCESSING BIASES
Bias Due to Decision Environment: • Complexity• Emotional Stress• Social Pressure
Bias from Information Sources • Consistency• Data Presentation
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BIASES RELATED TO OUTPUT
• Response Mode• Question Format• Scale Effects• Wishful thinking• Illusion of control
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BIASES RELATED TO FEEDBACK
Outcome irrelevant learning structure: • Personnel selection: No information of the
rejected candidates• Gambler’s Fallacy: Misperception of chance
Fluctuations• Success/Failure Attribution: Success to Hard
work/ Failure to Hard Luck.
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BIASES RELATED TO FEEDBACK
• Logical Fallacy in Recall: Eyewitness testimony may be wrong!
• Hindsight Bias: Decision-makers are usually not surprised about past happiness or good results, they can always find plausible explanations for them.
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Module-5
SOFTWARE DEVELOPMENT MODELS
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Software Development Life Cycle
Planning
Analysis
Design
Implementation
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Waterfall Models Planning + Feasibility
Requirement Analysis
System Analysis
System Design
Testing + Implementation
Coding
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Prototyping Identify Basic Information Requirements: Basic NeedsScope of ApplicationEstimated Cost
InitialPrototype
UserSatisfied ?
Develop the Initial Prototype
Use Prototype and Refine Requirements
OperationalPrototype
WorkingPrototype
EnhancedWorking
Prototype
NoYes
Revise and EnhancePrototypeUse Prototype as
Application Specification
Use Prototype as Application
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Software Development Models
Waterfall Models• Lack of iteration• Poor requirement gathering• Phase containment of errorsPrototyping• Quick user review• Quick development• Low development discipline
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Software Development Models
Rapid Application Development• Phased Development• Prototyping• Throwaway Prototyping
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Spiral Model
Planning Risk Analysis
CustomerEvaluation
Engineering
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Software Development Life Cycle
The Planning Stage• Project Initiation• Feasibility Analysis• Project Management
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Software Development Life Cycle
Feasibility Analysis• Technical Feasibility• Economical Feasibility• Organizational Feasibility
Project Management• Work Plan• Scheduling• Staffing• Controlling
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BPA/BPI/BPRBusiness Process Automation• Problem Analysis• Root Cause Analysis
Business Process Improvement• Duration analysis• Activity Based Costing• Benchmarking
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BPA/BPI/BPRBusiness Process Reengineering• Outcome Analysis• Technology Analysis• Activity Elimination• Proxy Benchmarking• Process Simplification
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System Analysis• System Study• BPA/BPI/BPR• Requirement Analysis• Use Case Modeling• Structural Modeling• Behavioral Modeling• Data Flow Modeling• Decision Analysis
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System Design• System Architecture Design• Hardware and Software, Computing
Architecture• User Interface Design• Input, Output, Forms, Control, Security,
Procedures• DBMS Design• Class and Methods Design• Program Design
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Implementation• Coding• Testing• Unit Testing, Integration Testing, System
Testing – alpha, beta etc.• Documentation• Installation• Planning, Testing, Changeover• Maintenance
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Requirement Analysis Basic Process of System Analysis• Understand the existing system• Identify improvements• Develop a conceptual framework for the
new system
Study ofStakeholders – Needs – Constraints –
Alterables
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Requirement Analysis • What problems to tackle?• Why solve the problem?• What are the solutions?• What complexities to resolve?• What are the inputs and the outputs?
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Requirement Analysis It is important to:• Understand requirements• Resolve anomalies, conflicts, and
inconsistencies• Organize requirments
The idea is to obtain what the system must do and not how to do it.
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The System Analyst The system analyst must possess:• Knowledge of the organization• Ability to grasp abstractions, group them
logically, and synthesize solutions• Systems thinking ability• Communication skills• Sound hardware and software knowledge
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Requirement Analysis Five Commonly-used techniques• Interviews• Joint Application Design• Document Analysis• Observations• Questionnaires
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Interviewing • Selecting interviewees.• Designing questions
• Open-ended• Closed-ended• Probing questions
• It is important to be very specific to operational management level interviews
• Take copious notes – be brief and attentive – watch body language – define your goal – define your belief and confirm.
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Joint Application Design• Can reduce the scope creep• Structured group process with 10-20 users• Used technology - white boards – flip
charts, computer etc.• Top down approach• Uses Nominal Group Technique with the
help of a facilitator• Should be carefully prepared – should
have a formal agenda
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Joint Application DesignRole of facilitator• Stick to agenda• Help understand technical terms• Record the group’s input publicly• Should always be neutral• Should not participate
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Joint Application DesignThings to note• Avoid Domination of individuals• Non-contributors are encouraged• Do not allow side discussions• Agenda merry-go-round be avoided• Violent agreement be avoided• Unresolved conflicts – structure the issue• True conflict – postpone• Use humour• Finally prepare JAD post-session report
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Questionnaires• Should be unambiguous• Preliminary opinions be sought• Provide anonymity to the respondents• Avoid biased or suggested items• Prepare reports
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Document Analysis and Observations
Document analysis• Format documents – forms, reports, and
manuals• Informal documents – both blank and
completed forms Observation• Remember not to interrupt the process • Look for anomalies
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Comparing TechniquesCriteria Interviews Joint
Application Design
Questionn-aire
Document Analysis
Observa-tions
Type of Information
Existing, Improved,
New
Existing, Improved,
New
Existing, Improved
Existing Existing
Depth of Information
High High Medium Low Low
Breadth of Information
Low Medium High High Low
User Involvement
Medium High Low Low Low
Cost Medium Low to Medium
Low Low Low to Medium
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Module-6
SYSTEM ANALYSISAND DESIGN
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DFD CASE STUDYBuying and Selling CompanyCustomers:• place orders for itemsThe Company:• keeps record of its regular customers• Names and Addresses• History of Purchases
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DFD CASE STUDYWhen an order is receivedAccounts department checks • credit-worthiness of the customer from past
recordsBad credit-worthiness• order is rejected along with a rejection message. Good Credit-worthiness• Items ordered are checked against a list of items
that the company deals with.
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DFD CASE STUDYItems not found on the list• Send regret message to the customer. Items found on the list• ordered items are checked for availability in the
inventory held
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DFD CASE STUDYItems are not available in required quantity• items along with the customer order details are
stored separately as pending orders Items are available in required quantity• Items are sent to the customer along with a
packing slip and an invoice. • Inventory is updated with the sales amount• Generate sales statistics
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DFD CASE STUDYThe purchase department:• issues item requests periodically. • Check against the pending orders• determine total quantity required for each items.• Check The supplier details The purchase department• generate purchase orders for the items to suppliers.
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DFD CASE STUDYThe management• Makes queries with regard to statistics of sales and
purchases.
The Buying and Selling Company• Answers to management queries
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DFD CASE STUDY
Item Order
Invoice +Delv. Adv.
Orders Query
Item Req.
Rej. MsgStatistics
Customers Buy & Sell Information
System
Suppliers
Manage-ment
Purchase Dept.
The Context Diagram
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Rej. Msg.
Customer File
Inventory
Item File
Accepted Order
Accept Order
CustomersOrders Customer
History
DFD CASE STUDY
Process: Accept Order
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Customer File
Rej. Msg.
Rej. Msg.
Checked Order
Credited Order
InventoryItem File
Accepted Order
Check Credits
Customers OrdersCustomer History
Check Items
Accept Order
DFD CASE STUDY
Detailed DFD for Accept Order
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DFD CASE STUDY
Process: Process Order
Invoice + Delivery Advice
Pending Orders
Inventory
Accepted Order
Process Order Sales
Statistics
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DFD CASE STUDY
Processes: Process Item Req. & Make Purchase Order
Supplier List
Pending Orders
Item Order
Item Req.
Process Item Req.
Supp-liers
Purchase Dept.
Make Purchase Orders
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DFD CASE STUDY
Process: Handle Query
Statistics
Management
Sales Statistics
Query
Handle Query
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TOP LEVEL DFD
Rej. Msg.
Supplier List
Pending Orders
Statistics
Inventory
Item Order
Item File
Invoice + Delivery Advice
Accepted Order
Accept Order
Process Order
Customers ManagementOrders
Customer History
Sales Statistics
Query
Item Req.
Process Item Req.
Suppliers
Customer File
Handle Query
Purchase Dept.
Make Pur. Orders
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DFD CASE STUDY: QUESTIONS
Consider the Detailed DFD of Accept Order
Find Attributes of:• Orders Rejected Order• Credited Order Checked Order• Accepted Order
Find Attributes of:• Customer File Customer History• Item File Inventory
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DFD CASE STUDY: QUESTIONS
Consider the Detailed DFD of Accept Order
Find Process Details for: • Check Credits• Check Items• Accept Order
Write Structured English statements.
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DATA DICTIONARY A collection of data element definitions. Important precursor to database design. Important fields:• Data element number • Data element name • Short description • Security classification of the data element • Related data elements • Field name(s) • Code format (Data type, size, input masks) • Null value allowed/Not allowed
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DATA DICTIONARYImportant fields (continued):• Default value • Allowed values for validation• Database table references • Definitions & References • Source of the data • Validity dates • History references • External references • Document Version • Document Date
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STRUCTURED ENGLISHCheck credit-worthinessIf the customer is credit-worthyThen Check Items ordered against a list of items
If the items are found on the list Then
Check availability of items in inventory If Items are available in required quantity Then
Items are sent to customer along with a packing slip and an invoice. Else
items with the order details are stored as pending orders
Endif Else
Send regret message to the customer. Endif
Elseorder is rejected along with a rejection message.
Endif
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STRUCTURED ENGLISH
Structured English Statements are shown for some of the processes of the DFD Case Study.
CHECK CREDIT
Check credit-worthinessIf the customer is credit-worthyThen
Check Items Else
send rejection message. Endif
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STRUCTURED ENGLISHCHECK ITEMSCheck Items ordered against a list of items If the items are found on the listThen
Accept OrderElse
Send regret message to the customer. Endif ACCEPT ORDERCheck the item in the inventory heldIf found
ThenAccept OrderElse
Update Inventory Accept Order
Endif
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STRUCTURED ENGLISHPROCESS ORDER Check availability of items in inventory heldIf Items are available in required quantityThen
Items are sent to the customer along with a packing slip and an invoice
Update Sales StatisticsElse
items along with the order details are stored separately as pending orders
Endif
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Module-7
DATABASE CONCEPTS
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DATABASE CONCEPTS• Database is a collection/single storage of all related data
files.• Database is a mechanized, centrally-controlled, collection
of data. • In a Database, Data are organized and stored in a manner
to promote shareability, availability, evolvability, and data integrity.
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WHY DATABASE• Problems of File Based Systems
• Data redundancy and inconsistency• Difficulty in accessing data• Data isolation• Concurrent access anomalies• Security problems• Integrity problems
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DATABASE CHARACTERISTICS• Co-ordinated Updation• High Quality and Recency of Data• Data Security• Data Compatibility• No Data Duplication• Logical Concept
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DATABASE CHARACTERISTICSCriteria
Conventional
FilesRelational Databases
Ease of Use Easy ComplexData Duplication Present Reduced
Data Sharing None Shared DataUpdate Anomaly Inconsistency NoneData Integration Absent IntegratedInitiating Change Hard Easy
Flexibility & Scalability
None Present
Cost Less HighDesign Reqmts. Less High
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DB, DBMS, & DBA• DATABASE (DB)• A mechanized, centrally-controlled, collection of data.
• DATABASE MANAGEMENT SYSTEM • A SOFTWARE to manage the database Collection of
interrelated data and a set of programmes to access that data
• DATABASE ADMINISTRATOR (DBA)• A person representing organizational authority over the
Database.
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DBMS OBJECTIVES • Availability • Shareability• Evolvability• Data Independence• Data Integrity
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DBMS OBJECTIVES • Availability: Data should be available when the user wants
to use it for:• Efficient storage, updating & retrieval of data.• Purposeful information retrieval. • Shareability: Data shared across applications. • No data is owned by an application.• Minimisation of unplanned redundancy. • Evolvability: Database should evolve with time as
applications and query needs changes with time.
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DATA INDEPENDENCE• Data Independence • Users of Database establish their view of the data and its
structure without regard to the actual physical storage of the data.
• This is achieved by • Separating data from the programs• Providing facilities for different user views• Separating logical design and physical design
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DATA INDEPENDENCE• Data Abstraction• Physical level: How the data is actually stored• Conceptual level: What data & their relationship• View Level: Part of the actual data
• Physical Data Independence• Ability to modify physical scheme without causing application
programs to be rewritten.
• Logical Data Independence• Ability to modify conceptual scheme without causing the
application programs to be rewritten.
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DATA INTEGRITY• DBMS needs to establish:• uniform high level of data accuracy and
consistency. • Validation rules are to be applied to the database. • The information obtained from the stored data
must be in an integrated form to be useful for managing, planning, controlling, or decision making.
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DBMS • DataBase Management System (DBMS)
• A software system that makes the database operational – It performs the following functions:
• Defining a database schema• Creating a new database• Revising an existing database• Controlling a database
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DBMS • A DBMS should have facilities to:• Retrieve data• Generate reports• Revising Data Definitions• Updating Data, and• Building Applications• DBMS, a door to the physical database, defines:• All accesses and Access language facilities• Data validation and authorization checks• Query handing
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DBA • Database Administrator (DBA)• The organizational function that exercises control over the database.
• Role of DBA• Carrying out DBMS instructions and facilities • Granting Authorization for data access• Defining Storage Structures & Access Methods • Definition, Creation, Redefinition, and Restructuring of Database• Implementing Integrity Controls.
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DATA MANAGEMENT Database Query Language
Utility/Facility
Database DefinitionDatabase Creation
Database RedefinitionDatabase Restructure
Integrity Controls
Database ProgrammingLanguage Interface
Database
Application Programs
Non-programming Users
Programming Users
DBA
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DATA DICTIONARY• Repository of information about data. Sometimes it is simply called
Schema.
• Name of the data item and Source of the data.• Description – picture, range, edit, and validation criteria, security,
owners, number of occurrences. • Impact analysis: users, screens, programs, people.• Keywords for categorisation and searching of data.
Facilities of a data dictionary• Report Facility: Detailed reporting • Control Facility: Authority and documentation• Excerpt Facility: Test Data, Source code
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DATABASE LANGUAGESData Definition Language (DDL)• To specify a database scheme
Data Manipulation Language (DML)• To retrieve, insert into, delete or modify data on a database
Procedural DML• Specify what data and how to get it
Nonprocedural DML• specify what data only.
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DATABASE ORGANIZATIONS• Flat File Approach• Hierarchical• Network• Relational
• Flat File Approach• A flat-file consists of records without repeating groups.
A table of records for rows and attributes for columns.
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HIERARCHICAL• In a hierarchical database the data is organized in a tree
structure. • Each parent record may have multiple child records, but
any child may only have one parent. • The parent-child relationships are established when the
database is first generated, which makes later modification more difficult.
• High processing efficiency but the response to query may be very slow if query is not in the same structure.
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NETWORKA network database is similar to a hierarchical database
except that a child record (a "member") may have more than one parent (an "owner").
• Parent-child relationships must be defined before the database is put into use.
• Addition or modification of fields requires the relationships to be redefined.
• Relationships between entities are represented by multiple pointers as well as link nodes.
• Complexity is high.
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RELATIONALIn a relational database the data is organized in tables that
are called "relations."
• Tables are usually depicted as a grid of rows ("tuples") and columns ("attributes").
• A set of tables/rows represent unique records/ entities and columns represent attributes.
• Links between tables can be established at any time algebraically provided the tables have a field in common.
• Relationships are represented by common data values in different relations.
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COMPARISON• In hierarchical/network structure, the connections and
relationships are in the data structure with the help of connections and access paths.
• Relational structure is flexible and useful for ad-hoc queries, complex DDL/DML are not required.
• For predefined relationships, access paths are more efficient than general table operations. So for predefined queries, hierarchical/network structures are competitive.
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EXAMPLE – CASE 1.GRADE RECORD.• STUDENT-ID String 9.• STUDENT-NAME String 25.• COURSES-TAKEN (repeats 10)• SEMESTER String 4. • COURSE-NO String 5.• GRADE String 1.
• The record takes up 134 bytes. • There are 34 bytes for the student number and name plus 10 bytes for
each of the 10 courses. • Student ID is a unique key for this record.
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EXAMPLE – CASE 2.GRADE RECORD.• STUDENT-ID String 9.• STUDENT-NAME String 25.• SEMESTER String 4. • COURSE-NO String 5.• GRADE String 1.
• This record consists of 44 bytes.• If a student takes ten courses then there will be a total of 10 records, for
a total of 440 bytes. • Student ID plus Semester and course-no would constitute a unique key.
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EXAMPLE – CASE 3.• GRADE RECORD. STUDENT-RECORD.• STUDENT-ID String 9. STUDENT-ID String 9.• SEMESTER String 4. STUDENT-NAME String 25.• COURSE-NO String 5.• GRADE String 1.
• The repetition of the student’s name is eliminated. • Student ID would serve as a common key. • Grade record is now 19 bytes and the Student record is now 34 bytes. • A student taking 10 courses would need 10 Grade records, for a total of 190
bytes.
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E-R DIAGRAM – EXAMPLE
M1
MORDER
VALUEDATE
NO.
PRICE-QTD.
O-S SUPPLIER
O-P
NAME
PRICEQTY-ORD.
ADDR
NN
PART
S-P
N
QOH NO.
NO.
NAME
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E-R DIAGRAM – EXAMPLE
1
N
PassengerName
Addr.Id. No. Phone
HAVE
Flight
Departure
Are Of
Date
SourceDest.
No.
Freq. Arr Time
Dep Time
N
1
Personnel
Are InM
N
SalName
Addr.ID
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DESCRIBING DATA• Data abstraction - Data model is abstract• Data models do not relate to flow of data
• Levels of Data description
• First level: Conceptual Data Model Development using Entity-Relationship Diagramming
• Second Level: Normalization of the data elements
• Normalized Data Model is then converted to a Physical Database.
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E-R DIAGRAMMING • Entity: Distinct things in an enterprise
• Relationships: Meaningful interaction between Entities
• Attributes: Properties of entities and relationships
MSTUD. SUB.STSUB
Name ID
ADDR
NameID
N
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E-R DIAGRAMMING
Strong vs. Weak Entity Set• Account is a Strong Entity as its existence is not dependent on other
entities.
• Transaction is a Weak Entity as its existence depends on the existence of Account as well.
A/C Trans.LOG
Name Bal.
ID
DateID
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E-R DIAGRAMMING
Generalization• Pilot and Engineer are generalizations of Entity Employee.
• ISA depicts generalizations
Employee
Pilot
Name Salary
Engineer
ExpertiseFlying Hrs ISA
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E-R DIAGRAMMING Aggregation
Ternary Relationship
Employee
Equipment
work
Project
use
Customer
Branch
HAS Account
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NORMALIZATION• First Normal Form (1NF) or Flat File • No Composite attributes, No repeating groups • Every attribute is single and describes one property.
Example: • GRADE-RECORD. Not in 1NF• STUDENT-ID String 9.• STUDENT-NAME String 25.• COURSES-TAKEN (repeats 10 times).• SEMESTER String 4. • COURSE-NO String 5.• GRADE String 1.
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NORMALIZATIONRemoving composite/repetitive attributes, we get
GRADE-RECORD. This is in 1NF• STUDENT-ID String 9. Is it in 2NF?• STUDENT-NAME String 25.• SEMESTER String 4. • COURSE-NO String 5.• GRADE String 1.
Second Normal Form (2NF) • Remove Non-full or partial dependency from 1NF. • No non-key field is a fact about a subset of a key.• Every non-key field is fully dependent on the key.
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NORMALIZATION• The Grade Record is not in 2NF.• KEY? Student-ID + Semester + Course-No.• Student-Name is a fact of Student-ID only!
• To make it in 2NF, we have to split the tables into:
• GRADE RECORD. STUDENT-RECORD.• STUDENT-IDString 9. STUDENT-ID String 9.• SEMESTER String 4. STUDENT-NAME String 25.• COURSE-NO String 5.• GRADE String 1.
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NORMALIZATIONThird Normal Form (3NF)
• Remove transitive dependency from 2NF. • No non-key field depends on another non-key field.
• Are they in 3NF?
• Yes! Because no transitive dependency is present!
• GRADE RECORD. STUDENT-RECORD.• STUDENT-ID String 9. STUDENT-ID String 9.• SEMESTER String 4. STUDENT-NAME String 25.• COURSE-NO String 5.• GRADE String 1.
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NORMALIZATION3NF Example
• STUDENT-RECORD.• STUDENT-ID String 9. (Key Element)• STUDENT-NAME String 25.• Dept-ID String 2• Dept-Name String 25.
• No repeating groups – 1NF• No partial dependency – 2 NF• Transitive dependency? – Yes! Not in 3NF
• How to bring it in 3NF?
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NORMALIZATION• 3NF Example: TO bring it to 3NF, we should have,
• STUDENT-RECORD. DEPT.-RECORD.• STUDENT-ID String 9. Dept-ID String 2.• STUDENT-NAME String 25. Dept-Name String 25.• Dept-ID String 2.
Another Example• SUPPLIER-NUMBER, SUPPLIER-NAME, SUPPLIER-ADDRESS,
PART-NUMBER, PART-NAME, QUANTITY-ON-HAND, PRICE-QUOTED, ORDER NUMBER, ORDER DATE, ORDER-VALUE, PRICE, and QUANTITY-ORDERED.
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NORMALIZED TABLESORDER NUMBER ORDER NUMBERORDER DATE SUPPLIER-NUMBERORDER-VALUE
ORDER NUMBERPART-NUMBER PART-NUMBERPART-NAME QUANTITY ORDEREDQUANTITY-ON-HAND PRICE
SUPPLIER-NUMBER SUPPLIER-NUMBERSUPPLIER-NAME PART-NUMBERSUPPLIER-ADDRESS PRICE-QUOTED