Mis Presentation Final
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Transcript of Mis Presentation Final
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PRASANTA KUMAR SUNA
PRAVEEN KUMAR
RAHUL KUMAR SHARMA
RAJEEV RATAN SHARMA
RAJESH KUMAR
RAJNEESH RANJAN
RAJU KUMAR
SANDEEP KISHORE KUJUR
SANJAY KUMAR SINGH
SATYENDRA KUMAR
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Data: Flow of captured events or transactions
Information: Data organized into categories of
understanding
Knowledge: Concepts, experience, and insight that
provide a framework for creating, evaluating, and
using information. Can be tacit (undocumented) orexplicit (documented)
Data, Information and Knowledge:
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Organizational learning: Adjusting business
processes and patterns of decision making to
reflect knowledge gained through information
and experience gathered
Organizational Learning
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Knowledge Management
The system and managerial approach to
collecting, processing, and organizing
enterprise-specific knowledge assets forbusiness functions and decision making.
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What is knowledge management
system?? A management information system serves the
functions of planning, controlling, and decision makingby providing routine summary and exception reports.
A decision-support system combines data andsophisticated analytical models or data analysis tools tosupport semi structured and unstructured decisions.
Knowledge management systemsare systems that
support the creation, capture, storage, anddissemination of firm expertise and knowledge.
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Knowledge acquisition
Knowledge storage
Knowledge dissemination
Knowledge application
Building organizational and management capital:collaboration, communities of practice, and officeenvironments
The Knowledge Management Value Chain
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Tools for Knowledge Management
1 Data base management tools
2 Data warehousing, Data mart and Data mining tools
3 Process modeling and Management tools
4 Work flow management tools5 Search engine tools
6 Document management tool
7 Web based tools
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Knowledge Management System
Architecture
Communication service
Storage service
Back bone layer
Data storage layer
Information storage layer
Analysis serviceKnowledge
creation/InformationAnalysis layer
Distribution applicationservice layer
Transport Service
Presentation Service
Transport Layer
Security layer
User interface layer
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Driving forces behind KM
External forces-
Globalization of business
Demanding customers Innovative competitors
Resourceful vendors
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Driving forces behind KM
Internal Forces-
Bottlenecks in effectiveness
Technological capabilities Understanding of human cognitive functions
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Key aspects of Knowledge management
Accelerating Knowledge creation and
application.
Converting tacit into Knowledge.
Build knowledge Assets-IC
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Misconceptions about KM
KM is an additional function and a high overhead.
KM require substantial investment in hardware and software.
Information set, once declared as knowledge, persists forever.
Knowledge has to be secret and can not be shared. It is a secret
formula, process. It should be with one or two personnel called
as confidential and should be stored in an inaccessible place.
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Misconceptions about KMPeople do not like to share knowledge, more so the knowledge
which gives them power in organization.
Knowledge once created, its use is automatic straight with
assured benefits.
KM leads to more additional work.
Knowledge is an analytical information, processed for specificgoal.
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Knowledge based Expert System (KBES)
Knowledge based expert system is an approach
towards solving problem in different situations on
the basis of stored knowledge database through
reasoning process by inference mechanism.
Characteristics:
1. Contain stored knowledge base.
2. Solve problems like humans.
3. Intelligent information processing systems.
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Basic independent components of KBES:
e BaseUser Control Mechanism
Knowledge Base Inference Mechanism
1. User control mechanism control entire processing mechanism by
using Knowledge base and guiding the Inference process.2. Knowledge base consisting of rules, formulas, facts, experience
etc.
3. Inference Mechanism is a tool to interpret the knowledge available
and to perform logical action in given situation.
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Method of Knowledge Based Expert
system
1. Semantic Network
2. Frames
3. Rules
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Semantic network
Knowledge is represented on the principle of
predicate functions and the symbolic data
structure which have meaning built into it are
semantic.
A network of notes and arcs connecting the
notes.
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Frames
To put the related knowledge in one area in an
organized data structure of a knowledge.
It consists of the slots representing a part of theknowledge.
Each slot form of data has a value and
expressed in the form of data information,process and rules
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Frame -: Engine over heating
Temperature more than 80 degree
Water boiling
Speed retardation
Slot :Symptomvalue
Check water level
Check oil engine
Check carburetor
Slot: InspectionValue
Stop engine and drain water Start engine and pour cold water
Increase oil level
Adjust carburetor
Slot :Treatmentvalue
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Rules
Method of representing the knowledge is rule
based.
A rules is a conditional statement of an action
that supposed to take place, under certain
condition ,that is If-Then
Eg. If an item is made of tungsten carbide.
Then the item is excisable
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Approaches to KM
Knowledge is intangible, dynamic, anddifficult to measure, but without it no
organization can survive.
Tacit: or unarticulated knowledge is morepersonal, experiential, context specific, and
hard to formalize; is difficult to communicate
or share with others; and is generally in the
heads of individuals and teams.
Explicit: explicit knowledge can easily be
written down and codified.
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Barriers at four different locations
KMS become successful in the organization when developers andusers recognize and appreciate the barriers in the systemimplementation. The barriers however loose the strength whencompetitive processes force organization to come out to these
barriers.
People In the organization
Resistance to change
Lack of motivation to learn
Turnover of people
Resistance to share knowledgeOrganization structure
Complex, distributed, based on different principles of structuringposing in storing, distribution sharing and security.
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Contd
Management of the organization
Ego problem
Loss of power of possession
Fear of loosing to competition
Knowledge itself
Decision on specific knowledge to declare it as a
general knowledge Unanimity in coding, classifying and storing of
knowledge
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MIS and KM
Knowledge is a result of putting different informationsets together and analyzing them, and viewing them in
particular manner. Information has a surprise valuewhile knowledge provides a vision to solve the problem
or understand the upcoming scenario. Data processing, transaction processing, application
processing systems will give different information sets.KMS on processing these information sets, first will
give and explicit knowledge. Further application of theexplicit knowledge over a period to solve the problemcreates a tacit knowledge.
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Contd.
Modern MIS not only should provide informationbut also support management by providingknowledge necessary at all levels for criticaldecisions. A knowledge generating KMS is now a
part of MIS suite. The traditional business model make and sale
changed to sense and respond as customerbecome more knowledgeable. for sense and
respond model only information is not adequatewhat is required is a knowledge, an ability toforecast the problem expectations.
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KM Software Tools
Globalserve
Knowcorp
Hyperknowledge
MicroStrategy
The Molloy Group
KnowledgeX Inc.
WebFarming.com
Softlab Enabling Tools
Imagination
Excalibur
Technologies
Imaging Solutions
Grapevine
Technologies
Intraspect Software
Milagro: The Power
of Imagination
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