It is used to process the computer data............

1. Presented by-
Ayisha kowsar A
MBA

2. 

4.  Definition : “TPS is type of Information System (IS) that
collects, stores modifies retrieves the data transaction of an
enterprise”
 Features of TPS:
 Rapid Response : fast performance with rapid
results
 Reliability : well developed with strong backup
and recovery and low failure rate
 Inflexibility : treats all the transactions equally,
but the transaction are to be precise
 Controlled Processing : roles and responsibilities
are well defined
Transaction Processing System

5.  5 types
 Master File
 Major information is stored in databases of master file
 Transaction File
 Collects transaction Records
 Updates master file
 Report File
 Contains data with formatted presentation to user
 Work File
 Temporary files in the system used during processing
 Program File
 Contains instructions for the processing of data
Type of Files in TPS

6. 

7. 
 Transaction Processing Systems can be broadly
classified into two types. They are
 Batch Processing
 Real time Processing/Online Processing
Types of TPS

8. 
 It is also called as Online Real Time Processing
System (OLRT)
 Input data is processed with immediate outputs
Real Time Processing

9. Real time processing is where all details of the transaction
are recorded and changed at the time as it occurs Eg: ATM

10. Advantages
The transactions are grouped into a transaction
file
The batch is then read in an order by the TPS
program
TPS often reads the stored data called master
data, process that master data, then creates a
new master data
It generates Reports during its process
Batch Processing

11. 
Dis-Advantages
Pre-determined process schedule
Correction of errors is impossible
during processing of data
Sorting Transaction data
Expensive and time consuming
Batch Processing

12. • useful for enterprises that need to process large
amounts of data using limited resources
• Batch processing is where the information is collected as
a batch and then processed later on. Eg: cheque.

13. 
Characteristics of TPS
 Large amounts of data are processed.
 The sources of data are mostly internal, and the
output is intended mainly for an internal audience.
 The TPS processes information on a regular basis:
daily, weekly, monthly, etc.
 Large storage (database) capacity is required.
 High processing speed is needed due to the high
volume.
 TPS basically monitors and collects past data.
Contd.,

14. 
 Input and output data are structured (i.e.,
standardized).
 Low computation complexity is usually evident in TPS.
 A high level of accuracy, data integrity, and security is
needed.
 High reliability is required.
 Inquiry processing is a must.
 To perform TPS the event should pass ACID test
Characteristics of TPS

15. 
ACID properties of TPS
Transactions are known as atomic, meaning that the
transaction will either happen or not. If one account is
debited, then another account has to be credited.
Atomicity:- all transactions/operations must
succeed or fail as a group.
Consistency:- all parties must agree on the
facts of the exchange
Isolation:- transactions must be independent
of each other.
Durability:- the effects of a completed
transaction should be lasting

16.  Databases are always protective , as they are delicate and has
restricted view of certain data. The structure of data is in 3
different forms
Databases and Files in TPS
Hierarchical Structure Network Relational

17. 
 Order Processing
 Purchasing
 Accounts Receivables & Payables
 Inventory & Shipping
 Payroll
TPS Applications

19.  Definition: “OAS is a computer based IS that collects, process,
stores and transmits electronic messages”
 Office automation refers to the varied computer machinery
and software used to digitally create, collect, store,
manipulate, and relay office information needed for
accomplishing basic tasks.
 Raw data storage, electronic transfer, and the management
of electronic business information comprise the basic
activities of an office automation system. Office automation
helps in optimizing or automating existing office
procedures.
Office Automatation

20. 
Basics of OAS

21. 
 Electronic Publishing
 Electronic Communication (E-mail, Fax, Video Conference)
 Electronic Collaboration
 Image Processing
 Office Management
 To support the above systems requirement of LAN
Functions Integrated by OAS

22. 
 Includes Word processing and DTP
 Create, edit, update, store and print documents,
letters, memos, reports
 Eg: MS Word, Corel Draw, Adobe Photoshop ,
Adobe PageMaker etc.,
E-Publishing

23. 
 E-mails ( Ms-Outlook, Lotus Mail, etc
 Fax (Facsimile)
 Voicemail
 Video Conferencing
E- Communication

24. E-mail is software that allows users, via their computer
keyboards, to create, send, and receive messages and
files to or from anywhere in the world.
create and save drafts of messages; send "carbon
copies"; and request automatic confirmation of the
delivery of a message.
 E-mail is very popular because it is easy to use, offers
fast delivery, and is inexpensive. Examples of e-mail
software are Eudora, Lotus Notes, and Microsoft
Outlook.
E- Mail

25. Voice mail is a sophisticated telephone answering
machine.
 It digitizes incoming voice messages and stores
them on disk. When the recipient is ready to listen,
the message is converted from its digitized version
back to audio, or sound.
Recipients may save messages for future use,
delete them, or forward them to other people.
Voice Mail

26. 
A facsimile or facsimile transmission machine (FAX)
scans a document containing both text and graphics
and sends it as electronic signals over ordinary
telephone lines to a receiving fax machine.
 This receiving fax recreates the image on paper. A
fax can also scan and send a document to a fax
modem (circuit board) inside a remote computer.
The fax can then be displayed on the computer
screen and stored or printed out by the computer's
printer
Facsimile

27. 
Desktop videoconferencing is one of the fastest
growing forms of videoconferencing.
 Desktop videoconferencing requires a network and
a desktop computer with special application
software (e.g., Microsoft Lync-2010) as well as a
small camera installed on top of the monitor.
 Images of a computer user from the desktop
computer are captured and sent across the
network. This type of videoconferencing simulates
face-to-face meetings of individuals.
Desktop Video Conferencing

28. Electronic collaboration is made possible through
electronic meeting and collaborative work systems
and teleconferencing.
Allows teams of coworkers to use networks of to
share information, update schedules and plans, and
cooperate on projects regardless of geographic
distance.
Special software called groupware is needed to
allow two or more people to edit or otherwise work
on the same files simultaneously.
Electronic Collaborations

29.  Image processing systems include electronic document
management, presentation graphics, and multimedia systems.
 Imaging systems convert text, drawings, and photographs into
digital form that can be stored in a computer system. This
digital form can be manipulated, stored, printed, or sent via a
modem to another computer.
 Imaging systems may use scanners, digital cameras, video
capture cards, or advanced graphic computers.
 Companies use imaging systems for a variety of documents
such as insurance forms, medical records, dental records, and
mortgage applications.
Image Processing

30.  Office management systems include electronic office
accessories, electronic scheduling, and task management.
 These systems provide an electronic means of organizing
people, projects, and data. Business dates, appointments,
notes, and client contact information can be created, edited,
stored, and retrieved.
 Projects and tasks can be allocated, subdivided, and planned.
All of these actions can either be done individually or for an
entire group. Computerized systems that automate these
office functions can dramatically increase productivity and
improve communication within an organization.
Office Management

31. 
Advantages of OAS

32. 
Disadvantages of OAS

34. 
Definition: “It is an interactive computer based system
that helps decision makers to utilize the data and model
to solve the unstructured problems”
Components of DSS
 User Interface
 Database
 Models and analytical tools
 DSS Architecture and network
Decision Support System

35. 
Architecture of DSS

36. 5 types
 Model Driven : manipulation of statistical, financial
optimization for simulation models
 Communication Driven : supports more than one person
working on a shared task
 Data-Driven : first generic type based on TPS
 Document-Driven : manages, retrieves, manipulates
unstructured information
 Knowledge-Driven : provides specialized problem
solving expertise
Classification of DSS

37.  Ability to support solution for complex problems
 Quick response during unexpected situations , that results in
change of inputs
 Constructed to support one time decisions
 DSS is designed for group / single decision makers
 DSS design software can be used
 Consistent and Objective decisions
 Other Characterstics:
 Cost saving, graphical display , designed and run by mangers
Characteristics of DSS

38. 
 Improves personal efficiency and organizational control
 Speed up the process of problem solving & Decision Making
 Promotes learning and training
 Generates new evidence in support of a decision
 Creates a competitive advantage over competition
 Helps automate managerial process
Advantages of DSS

40.  GDSS = Elements of DSS + Software
 To provides an effective decision making settings.
Characteristics of GDSS
 Special Decision
 Ease of Use
 Flexibility
 Decision Making Support
 DELPHI method (Decision Makers are Geographically
Dispersed)
 Brainstorming
 Nominal Group Technique
Group Decision Support System

41. Characteristics of GDSS
 Anonymous Input
 Reduction of Negative Group Behaviour
 Parellel communication
 Automated Record Storage
 Cost Control Complexity factors
Group Decision Support System

42. 
Alternatives of GDSS

43. Description MIS DSS
Focus
Structure task and
Routine
Semi-Structured Task,
requiring managerial
judgement
Emphasis Data Storage Data Manipulation
Data Access Indirect Access by
Managers
Direct Access by
Managers
Reliability On Computer
expert
Self-decision by
Managers
Nature of
Decision
U known Decision
Environment
Known Decision
Environment
Execution On Efficency On Effectiveness
Differences between MIS & DSS

45.  Definition : “A specialized DSS that includes hardware,
software, data, procedures, and people to assist top level
executives with in an organization”.
 Expert systems are also called as knowledge based system
 A computer based system that serves the information needs
of top level management
 Provides quick access to timely information
 Direct access to management reports
 User-friendly and supported by graphical representation
(charts)
 Easily connected to internet
ESS/EIS/ES

46. 
Drill Down
Critical Success Factors
Status Access
Analysis, Exception Reporting
Navigation of Information and Communication
(colours, audio and video)
Characteristics of EIS/ESS

47. 
Architecture of EIS/ESS

48. 
 Availability
 Cheaper
 Reduce Danger
 Permanence : - knowledge with last long indefinitely
 Multiple expertise's
 Explanation
 Fast Response
 Unemotional and response at all times
Advantages of ESS/EIS

49. 
 No common sense needed in some decision making
 Cannot respond creatively like human expert
 Domain experts are not always able to explain their
logic and reasoning
 Errors may occur in the knowledge base, that lead to
wrong decisions
 Cannot adopt changing environments, unless
knowledge base is changed
Disadvantages of EIS/ESS

51.  Definition : “Data Security refers to protective measures to
prevent unauthorized access to the computers , databases,
websites”.
 Information System Concerns :
 Unintentional threats
 Human error – in design and use of the system
 Environmental Hazards – acts of God and other
 Computer system failure – faulty products
 Intentional threats
 Hacking, Criminal attacks, Cyber attacks
Data Security

52.  Prevention :
 Prevent computer for information violations from occurring
Eg: loosing password, forget to logout, disclosing of pin
 Detection :
 Identification the assets of attack
 How the attack has occurred
 When it has occurred
 By whom the attack is made
Eg: I LOVE U Virus
 Response :
 Developing techniques and strategies to combat attack
Goals of Information Security

53. 
Risk to IS
Contd.,
Risk to Information
Systems
Application & Data Hardware

54. a) Computer crime:
 Unauthorized copying of information/sotware.
 Unauthorized use of access, modify, destruct hardware/
software/network resources.
 Deny the end user access of his or her own
data/software/network
b) Hacking:
 Illegal hackers are also called as crackers
 Can monitor, e-mail, passwords, file transfers etc., and steal
them unauthorized by entering into the network.
 Use of remote services to allow one computer to execute tasks
on another computer using network privileged access
Risk to Application and Data
Contd.,

55. c) Cyber-Theft:
 Theft of money.
 Unauthorized network entry, fradulent alternation of
database Eg: modifying employee master data etc.,
d) Software Piracy
 Unauthorized copying of software (as software is intellectual
property)
 Software is protected by copyright law and EULA (End User
Licensing Aggrement)
Risk to Application and Data
Contd.,

56. e) Computer Viruses & Worms:
 Virus : “A piece of code which is capable of copying itself and
typically has a detrimental effect, such as corrupting the system or
destroying data”
 Worm : “A computer worm is a standalone malware computer
program that replicates itself in order to spread to other
computers”.(uses network for replication)
Risk to Application and Data
Contd.,

57. a) Natural Disaster :causes partial paralysis of systems and
communications
 Floods
 Hurricanes
 Fires
 Earthquakes
b) Blackout and Brownout:
 Blackout – loses of electrical power
 Brownout – short interruptions in flow of power
 Vandalism – human deliberately destroy the system
Risk to Hardware
Contd.,

58. 
 Encryption
 Authentication
 Firewalls
 Virus Defenses (Antivirus)
 Backup files
 Security Monitors
 Biometric controls
 Disaster Recovery
Major types of Defense Strategies

59.  9 steps
 Obtain management commitment to plan
 Establish a planning committee
 Perform risk assessment and impact analysis
 Set priority for recovery needs
 Recovery plan methods
 Identify Vendors (who can do this job effectively)
 Develop, Test, Implementation Plan
Business Recovery Plan

61.  Definition: “A warehouse is a Subject Oriented, Integrated,
Time-Variant, Non-Volatile collection of data in support of
decision making process by management”
 Subject Oriented : Data that gives information about a
particular subject instead of about a company's ongoing
operations.
 Integrated : Data that is gathered into the data warehouse
from a variety of sources and merged into a coherent whole
 Time-Variant : All data in the data warehouse is identified
with a particular time period.
 Non-Volatile : Data is stable in a data warehouse. More
data is added but data is never removed. This enables
management to gain a consistent picture of the business.
Data Warehouse

62. 
Data Warehouse—Subject-Oriented
 Organized around major subjects, such as customer,
product, sales.
 Focusing on the modeling and analysis of data for
decision makers, not on daily operations or transaction
processing.
 Provide a simple and concise view around particular
subject issues by excluding data that are not useful in the
decision support process.

63. 
Data Warehouse—Integrated
 Constructed by integrating multiple, heterogeneous
data sources
 relational databases, flat files, on-line transaction records
 Data cleaning and data integration techniques are
applied.
 Ensure consistency in naming conventions, encoding
structures, attribute measures, etc. among different data
sources
 E.g., Hotel price: currency, tax, breakfast covered, etc.
 When data is moved to the warehouse, it is converted.

64. 
Data Warehouse—Time Variant
 The time horizon for the data warehouse is significantly
longer than that of operational systems.
 Operational database: current value data.
 Data warehouse data: provide information from a historical
perspective (e.g., past 5-10 years)
 Every key structure in the data warehouse
 Contains an element of time, explicitly or implicitly
 But the key of operational data may or may not contain “time
element”.

65. 
Data Warehouse—Non-Volatile
 A physically separate store of data transformed from
the operational environment.
 Operational update of data does not occur in the data
warehouse environment.
 Does not require transaction processing, recovery, and
concurrency control mechanisms
 Requires only two operations in data accessing:
 initial loading of data and access of data.

66. Data Warehouse: A Multi-Tiered Architecture
Data
Warehouse
Extract
Transform
Load
Refresh
OLAP Engine
Analysis
Query
Reports
Data mining
Monitor
&
Integrator
Metadata
Data Sources Front-End Tools
Server
Data Marts
Operational
DBs
Other
sources
Data Storage
OLAP Server

67. 
Types of OLAP Servers
( Partition Storage Modes and Processing )
4 types of OLAP Servers
Relational OLAP (ROLAP)
Multidimensional OLAP (MOLAP)
Hybrid OLAP (HOLAP)
Specialized SQL servers
Contd.,

68. 
OLAP Server Architectures
 Relational OLAP (ROLAP)
Placed between relational backend and client
front-end tools
To store and manage data ROLAP uses
Relational or extended- RDBMS
Include optimization of DBMS backend
Implementation of aggregation navigation
logic
Additional tools and services
Greater scalability
Contd.,

69. 
OLAP Server Architectures
ROLAP Architecture
Contd.,

70. 
OLAP Server Architectures
Advantages
ROLAP servers are highly scalable
Can be easily used with existing RDBMS
Data can be stored efficiently size zero facts
can be stored
ROLAP tools do not use pre-calculated data
cubes
DSS (Decision Support System) of micro-
statergy adopts ROLAP approach
Contd.,

71. 
OLAP Server Architectures
Dis-Advantages
Poor Query Performance
Some limitations of scalability depending on the
technology architecture that is utilized
Contd.,

72. 
OLAP Server Architectures
 Multidimensional OLAP (MOLAP)
 Array-based multidimensional storage engine for
views of data
 Process information with consistent response time
regardless of level of summarizing or calculations
selected
 MOLAP tools adopts two level of storage
representation to handle dense and sparse data sets
 Denser sub-cubes are identified and stored as array
structure
 Sparse sub-cubes employ compression technology
 Fast indexing to pre-computed summarized data
Contd.,

73. 
OLAP Server Architectures
 MOLAP Architecture
Contd.,

74. 
OLAP Server Architectures
Advantages
 Fastest Indexing to the pre-computed summarized
data
 Helps the users connected to the network need to
analyze larger and less defined data
 Best suitable for inexperienced users
Dis-Advantages
 Not capable of containing detailed data
 Storage utilization may be low if the data is set to
sparse Contd.,

75. 
OLAP Server Architectures
 Hybrid OLAP (HOLAP) (e.g., Microsoft SQLServer)
 HOLAP technique is a combination of both ROLAP &
MOLAP
 Has higher scalability of ROLAP
 faster computation of MOLAP
 HOLAP server allows to store large data volumes of
detail data
 Aggregations are stored in separate MOLAP Store
 Flexibility, e.g., low level: relational, high-level: array
Contd.,

76. 
OLAP Server Architectures
 Hybrid OLAP (HOLAP) (e.g., Microsoft SQLServer)
Contd.,

77. 
OLAP Server Architectures
 Advantages
 Combined advantages of both MOLAP and ROLAP
 combine the ROLAP technology for sparse regions and
storing detailed data
 MOLAP for dense regions, higher-level summary data
 Dis-Advantages
 Complex ROLAP must support both MOLAP &
ROLAP enginers
 Functionally overlap between ROLAP & MOLAP
Contd.,

78. 
Typical OLAP Operations
 Roll up (drill-up): summarize data
by climbing up hierarchy or by dimension reduction
 Drill down (roll down): reverse of roll-up
from higher level summary to lower level summary or
detailed data, or introducing new dimensions
 Slice and dice: project and select
 Pivot (rotate):
reorient the cube, visualization, 3D to series of 2D
planes

79. 
June 13, 2020 Data Mining: Concepts and Techniques 79
Fig. 3.10 Typical OLAP
Operations

81.  The non-trivial (small-importance)process of
identifying
 Valid
 Novel (new)
 Potentially useful
 Ultimately understandable patterns in data,
UNCOVER HIDDEN INFORMATION
DATA MINING
Data Mining

82. 
Alternative names:
 Data Fishing, Data Dredging (1960s)
 Data mining (1990s) used by DB and business
 KDD (Knowledge Discovery in Databases) used
by AI
 BI, Information Harvesting, Information Discovery,
Knowledge Extraction
Alternative NamesAlternative names of Data Mining

83. 
Relational databases
Data warehouses
Transactional databases
Advanced DB and information repositories
 Object-oriented and object-relational databases
 Spatial databases
 Time-series data and temporal data
 Text databases and multimedia databases
 Heterogeneous and legacy databases
 WWW
Data Mining : On What Kind of Data
Contd.,

84. 
Knowledge Discovery (KDD) Process
 Data mining—core of
knowledge discovery process
Data Cleaning
Data Integration
Databases
Data Warehouse
Task-relevant Data
Selection
Data Mining
Pattern Evaluation
Knowledge Discovery (KDD) Process
Contd.,

85. 
Data Cleaning: remove noise and inconsistent data
Data Integration : Combining of multiple resources
Data Selection : relevant data to analysis task, that
are retrieved from database
Data Transformation : convert to common format
then transform to new format
Data mining: Obtain desired results
Pattern Evaluation : data obtained with degree of
certainty or potential data
Knowledge presentation: present the mined
knowledge to the user
Note: KDD Process is iterative
KDD Process
Contd.,

86. Prediction e.g. sales volume, earthquakes
Identification e.g. existence of genes, system
intrusions
Classification of different categories e.g.
discount-seeking shoppers or loyal regular
shoppers in a supermarket
Clustering of identify groups of items that
share a particular characterstic
Goals or Functions of Data Mining and KDD
Contd.,

87. Association identify relationships between
events that occur at one time
Sequencing similar to association, except
that the relationship exists over a period of
time
Forecasting estimate future values based on
patterns with large sets of data (demand
forecasting)
Goals or Functions of Data Mining and KDD