Transcript No Slide Title

Business
Information
Systems
LEARNING
OBJECTIVES
© Arjan Raven and Duane Truex
1. Define and describe the repository
components of business information
systems (BIS): Production Databases,
Data Warehouse, Knowledge Repository
2. Define and describe the BIS applications:
TPS, MIS, OLAP (including
DSS/EIS/GDSS), Data Mining, Search
Engines, Content Editing and Production
Tools
3. Define and describe the relationships
between the repositories and applications
1
The B
usiness
S
ystems
Architecture
DSS,
GDSS
& EIS
Transaction
Processing
Systems
(TPS)
Management
Information
Systems
(MIS)
© Arjan Raven & Duane Truex
Content
Editing &
Production
tools
Search
Engines
& tools
On-line
Analytical
Processing
(OLAP)
(Deductive)
Production
Database
External
Data
Sources
Data
Warehouse
Data
Mining
(Inductive
reasoning)
Knowledge
Repository
Organizational
Memory
Information
System
(OMIS)
Collaboration
and
Coordination
tools
2
Definitions(1): Repositories
• Production Database
• A collection of pre-specified and highly organized(mostly) textual
data in a relational database.
• Used by TPS and MIS.
• Has to be very fast and robust
• Data Warehouse
• Like production database, a collection of pre-specified and highly
organized(mostly) textual data in a relational database.
• Can be slower
• Is not mission critical.
© Arjan Raven & Duane Truex
3
Definitions(2): Repositories, Continued
• Knowledge Repository
• Storage place for unstructured data and information
• Knowledge is in the linkages between the data and
information (e.g. hyperlinks, maps)
• Knowledge is retrieved through searches
• Search engines add intelligence to a knowledge
repository
• Two common implementations:
• Lotus Notes (Knowledge Roach Motel)
• Intranets
© Arjan Raven & Duane Truex
4
Definitions(3): Repositories, Continued
• External Data Sources
• Databases and knowledge repositories.
• Proprietary (paid)
• Public (free)
© Arjan Raven & Duane Truex
5
Definitions(4): Applications
• TPS (Transaction Processing System)
• An organized collection of people procedures, databases, and devices to record
completed business transactions
• Any business-related exchange
• MIS (Management Information Systems)
• An information system that provides aggregated, summarized information to
decision makers.
• Inputs typically is transaction data acquired from TPS
• Outputs are standardized, pre-specified reports
• OLAP (On-line Analytical Processing)
• Targeted query, the user knows exactly what she is looking for
• Used in Decision Support Systems (DSS), Executive Information
Systems (EIS) and Group DSS (GDSS)
• Collaboration and Coordination tools
• email, calendaring,electronic bulletin boards, groupware (Lotus Notes,
Groupwise…)
© Arjan Raven & Duane Truex
6
Definitions(5): Applications, Continued
• Organizational Memory Information System
• The collection of repositories and systems that together preserve an
organization’s history, and make it available for current and future use
• Data Mining
• You don’t know what you are looking for
• The mining software looks for patterns
• Uses automated statistical pattern matching algorithms
• Search Engines
• Tools that let you search through knowledge repositories
• Examples: Alta Vista, Excite
• New developments: natural language processing (Ask Jeeves);
Dynamically created concept maps
© Arjan Raven & Duane Truex
7
Definitions(6): Applications, Continued
• Content Editing & Production tools
• HTML Editors and site management tools:
• Dreamweaver, Frontpage, Netscape Composer
• Word Processors, (e.g. Word, Wordperfect)
• Multimedia presentation tools:
• Static: Powerpoint
• Dynamic/interactive: Dreamweaver
© Arjan Raven & Duane Truex
8
Business Information Systems in
Perspective
• Transaction processing systems provide the raw
material for the other types of information
system within most business organizations.
More
Decision Support Systems
Management Information Systems
More
Dependence
Complexity on external
data
Routine
Transaction Processing Systems
More
© Arjan Raven & Duane Truex
9
Transaction Processing System
• Transaction
• Any business-related exchange
• Transaction processing systems (TPS)
• An organized collection of people procedures, databases, and
devices to record completed business transactions
Hours
Worked
Payroll
Transaction
Processing
Payroll
Checks
Pay
Rate
© Arjan Raven & Duane Truex
10
Transaction Processing Systems
• Transactions
• Basic business activities such as customer orders,
time cards, and payroll checks
• TPS process the detailed data necessary to
update records about fundamental business
operations of an organization.
• Data should be captured at its source. It should
be recorded accurately, in a timely fashion, with
minimal manual effort, and in a form that can be
directly entered into the computer.
© Arjan Raven & Duane Truex
11
Characteristics of Transaction
Processing Systems
• Provide fast, efficient processing to handle
large amounts of input and output
• Perform rigorous data editing to ensure
that records are accurate and up to date
• Are audited to ensure that all input data,
processing, procedures, and output are
complete, accurate, and valid
© Arjan Raven & Duane Truex
12
Example of Source Data
Automation
Customer
Receipt
MIS
UPC
Scanner
Exception
Report
Point-of-Sale
TPS
Time,
date,
Inventory
quantity
Point-of-Sale Transaction Processing System
© Arjan Raven & Duane Truex
13
Management Information System
(MIS)
• An information system that provides
aggregated, summarized information to
decision makers.
• Inputs typically is transaction data
acquired from TPS
• Outputs are standardized, prespecified
reports
© Arjan Raven & Duane Truex
14
Management Information System
(MIS)
Marketing
MIS
Manufacturing
MIS
Common
Database
Financial
MIS
© Arjan Raven & Duane Truex
Other
MISs
TPS
15
Outputs of a Management
Information System
• Scheduled reports
• Produced periodically or on a schedule
(daily, weekly, monthly)
• Key-indicator report
• Type of scheduled report that summarizes the
previous day’s critical activities
• Typically available at the beginning of each
workday
continued...
© Arjan Raven & Duane Truex
16
Outputs of a Management
Information System
• Demand reports
• Developed to give certain information at a
manager’s request
• Exception reports
• Automatically produced when a situation is
unusual or requires management action
• Drill-down reports
• Provides increasingly detailed data about a
situation
© Arjan Raven & Duane Truex
17
Decision Support Systems
• An information system that supports different decision
making styles through on-the-fly queries and prespecified models, using data from internal and external
sources, presented according to user preferences
• Focus on decision-making effectiveness when faced
with unstructured or semi-structured business problems
• Decision Support Systems can help identify potential
mistakes and provide a structure that makes it more
difficult for a person to make a mistake.
• With the use of decision support systems, employees
risk losing touch with the underlying principles that guide
the enterprise.
© Arjan Raven & Duane Truex
18
Decision Support Systems
• Primary characteristic: performs different types
of analyses
• “What-if” analysis
• Makes hypothetical changes to problem and observes
impact on the results
• Simulation
• Duplicates features of a real system
• Goal-seeking analysis
• Determines problem data required for a given result
© Arjan Raven & Duane Truex
19
Conceptual Model of a DSS
Internal
Databases
Models
Bases
Model
Database
Management Management
System
System
Interface
to
External
sources
External
Databases
and
models
Dialogue Manager
User
© Arjan Raven & Duane Truex
20
Artificial Intelligence
• Artificial intelligence
• A field that involves computer systems taking on the
characteristics of human intelligence
• General Categories:
•
•
•
•
Expert Systems
Neural Networks
Case Based Reasoning
Collaborative Filtering
© Arjan Raven & Duane Truex
21
Components of Expert Systems
Inference
Engine
Subject
Knowledge
Base
Human
© Arjan Raven & Duane Truex
Knowledge
Acquisition
System
Subject
Domain
Experts
User Interface
and
Explanation
facility
User
Interface
User
22
AI Applications
• Years of overpromise and underdelivery, but
now new technologies:
•
•
•
•
Voice recognition
Optical character recognition
Handwriting recognition
Search engines
• Tangible results, e.g.
•
•
•
•
Credit Card Fraud Detection
Stock market prediction
Automated Helpdesks
Great/Annoying Personal Assistants in Office Suite
© Arjan Raven & Duane Truex
23
End of Business Information Systems
© Arjan Raven and Duane Truex
24