SlideShare a Scribd company logo
1 of 24
Data Mining & Warehousing
1 ) User expectation
2 ) Systems optimization
3 ) Data structuring
4 ) Prefabricated vs. Custom warehouse
5 ) Resource balancing
Challenges faced on Data
Warehousing
2
As the volume of data in a warehouse increases,
warehouse management systems need to move deeper in
warehouses for data analysis.
The end-user in these cases demands and expects more
accurate and refined results in return of processing,
however that is not the case with warehouse systems.
 The performance decreases with exploding data and so
the efficiency of the system reduces.
1. User expectation
3
Regressive utilization of business intelligence tools
require frequent maintenance and fine tuning of whole
system in order to meet users' expectations.
Carefully designed and configured data analysis tool
helps in providing better results for effective business
development decisions.
2. Systems optimization
4
Proper processing of data requires structuring it in a
desired format so that further operations can be
executed.
 As the volume of data increases the task of structuring
data of system eventually becomes hectic for the system
manager.
3. Data structuring
5
The varieties of warehouses available in market, create
ambiguity about which type to choose or go for.
Where custom warehouse saves the time of building the
warehouses from various operational databases from
weeks to days or even hours, prefabricated warehouses
saves the time of initial configuration and installation.
4. Prefabricated vs. Custom
warehouse
6
In order to draw benefit from data warehousing, most
departments inside an organization tend to access the
processing capabilities of the warehouse.
 This eventually reduces the performance of the system and
decreases the efficiency as the stress on the system increases.
Access control and security are some techniques which can be
used to maintain a balance between the utilization and
performance of warehouse systems.
5. Resource Balancing
7
 Decision support systems (DSS) are a specific class of
computerized information system that supports business and
organizational decision -making activities.
 DSS is a well integrated ,user friendly, computer based tools
that combine data with various decision making models to
solve semi structure and unstructured problems.
Decision support system
8
 Provide decision support for several interdependent decision.
 Assist the decision maker to make decision under dynamic
business conditions.
 Supports a wide variety of decision making processes and
style.
Characteristics
9
How a DSS works???
10
 Database management system
 Model management system
 Support tools
Components of DSS
11
 In database management ,the problem necessary to solve may
come from internal and external database.
 Within the organization, internal data are generated by
systems such as TPS and MIS; external data come from
variety of sources such as periodicals, databases, newspapers
and online data services.
Database Management
12
 It stores and access models that managers use to make
decisions.
 Models are integral part of most decision making and are
used for many tasks, such as designing a manufacturing
facility, analysing the financial health of an organization,
forecasting demand for a product or service, and determining
the quality of a particular batch of products.
Model Management Component
13
 It consist of tools such as pull down menus, on -line help,
users interface, graphical analysis and error -correction
mechanisms all of which facilitate users interactions with the
system.
 Interfaces are an important support tools. This is because
middle and top managers have neither the time nor the
inclination to learn difficult and complicated procedures in
order to run a system. For better the interface, the greater
the chances that users will accept the system.
Support Tools
14
 Cost saving
 Improve managerial effectiveness
 Flexible and adaptive
 Improve the effectiveness of the decision
 Reduces the time and efforts in collecting and analysis of
data for different sources, a large no of alternatives can be
evaluated.
Advantages of DSS
15
It is also termed as Executive Support System[ESS].
It is a specialized decision support system used to assist
senior executives in the decision -making process.
It includes various hardware, software, data, procedures and
the people.
It is very user friendly in the nature.
It is supported at a large extent by the graphics.
Executive Information System[EIS]
16
17
1. Informational characteristics
2. User interface/orientation characteristics
3. Managerial / executive characteristics
Characteristics of Executive
Information System
18
i . Flexibility and ease of use.
i i . Provides the timely information with the short response
time and also with the quick retrieval.
i i i . Produces the correct information.
i v . Produces the relevant information.
v . Produces the validated information.
1. Informational characteristics
19
i . Consists of the sophisticated self help.
i i . Contains the user friendly interfaces consisting of the
graphic user.
i i i . Can be used from many places.
i v . Offers secure reliable, confidential access along with the
access procedure.
v . Is very much customized. Suites the management style of the
individual executives.
2. User interface/orientation
characteristics
20
i . Supports the over all vision, mission and the strategy.
i i . Provides the support for the strategic management.
i i i . Sometimes helps to deal with the situations that have a high
degree of risk.
i v . Is linked to the value added business processes.
v . Supports the access to database.
v i . Is very much result oriented in the nature.
3. Managerial / executive characteristics
21
1.Achievement of the various organizational objectives.
2.Facilitates access to the information by integrating many
sources of the data.
3. Facilitates broad, aggregated perspective and the context.
4. Offers broad highly aggregated information.
5. User’s productivity is also improved to a large extent.
6. Communication capability and the quality are increased.
Advantages of EIS
22
1 . Internal factors - accurate & reliable information, improve
communications, use of historical data
2. External factors - increasing global competition, changing the
business environment, government regulations.
Factors affecting EIS
DSS EIS
 Used by professionals
 Required for day to day
operations
 Deals both with semi &
unstructured data
 Consists only of internal
information
 Used by executives
 Required for strategic plans and
procedures
 Deals only with unstructured
data (which cannot be described
in detail)
 Consists of both internal &
external information
24
Differences between DSS and EIS

More Related Content

What's hot

Introduction to data warehousing
Introduction to data warehousing   Introduction to data warehousing
Introduction to data warehousing
Girish Dhareshwar
 
Data warehouse architecture
Data warehouse architectureData warehouse architecture
Data warehouse architecture
pcherukumalla
 
Introduction to Data Warehouse
Introduction to Data WarehouseIntroduction to Data Warehouse
Introduction to Data Warehouse
Shanthi Mukkavilli
 

What's hot (20)

Data warehousing
Data warehousingData warehousing
Data warehousing
 
Introduction to data warehousing
Introduction to data warehousing   Introduction to data warehousing
Introduction to data warehousing
 
Chapter - 7 Data Mining Concepts and Techniques 2nd Ed slides Han & Kamber
Chapter - 7 Data Mining Concepts and Techniques 2nd Ed slides Han & KamberChapter - 7 Data Mining Concepts and Techniques 2nd Ed slides Han & Kamber
Chapter - 7 Data Mining Concepts and Techniques 2nd Ed slides Han & Kamber
 
Data warehouse
Data warehouseData warehouse
Data warehouse
 
Data warehouse
Data warehouseData warehouse
Data warehouse
 
Data mining tasks
Data mining tasksData mining tasks
Data mining tasks
 
Data warehouse architecture
Data warehouse architectureData warehouse architecture
Data warehouse architecture
 
Data warehousing
Data warehousingData warehousing
Data warehousing
 
Warehousing dimension star-snowflake_schemas
Warehousing dimension star-snowflake_schemasWarehousing dimension star-snowflake_schemas
Warehousing dimension star-snowflake_schemas
 
OLAP & DATA WAREHOUSE
OLAP & DATA WAREHOUSEOLAP & DATA WAREHOUSE
OLAP & DATA WAREHOUSE
 
Data preprocessing
Data preprocessingData preprocessing
Data preprocessing
 
Data preprocessing
Data preprocessingData preprocessing
Data preprocessing
 
Visual Analytics in Big Data
Visual Analytics in Big DataVisual Analytics in Big Data
Visual Analytics in Big Data
 
Introduction to Data Warehouse
Introduction to Data WarehouseIntroduction to Data Warehouse
Introduction to Data Warehouse
 
Data warehousing - Dr. Radhika Kotecha
Data warehousing - Dr. Radhika KotechaData warehousing - Dr. Radhika Kotecha
Data warehousing - Dr. Radhika Kotecha
 
DATA WAREHOUSING
DATA WAREHOUSINGDATA WAREHOUSING
DATA WAREHOUSING
 
Data analytics
Data analyticsData analytics
Data analytics
 
Data analytics vs. Data analysis
Data analytics vs. Data analysisData analytics vs. Data analysis
Data analytics vs. Data analysis
 
Data mining notes
Data mining notesData mining notes
Data mining notes
 
Data warehouse and data mining
Data warehouse and data miningData warehouse and data mining
Data warehouse and data mining
 

Viewers also liked (7)

Data warehousing and Data mining
Data warehousing and Data mining Data warehousing and Data mining
Data warehousing and Data mining
 
Data Mining and Data Warehousing
Data Mining and Data WarehousingData Mining and Data Warehousing
Data Mining and Data Warehousing
 
DATA WAREHOUSING AND DATA MINING
DATA WAREHOUSING AND DATA MININGDATA WAREHOUSING AND DATA MINING
DATA WAREHOUSING AND DATA MINING
 
data warehousing and data mining
data warehousing and data mining data warehousing and data mining
data warehousing and data mining
 
Session7part1
Session7part1Session7part1
Session7part1
 
introduction to data warehousing and mining
 introduction to data warehousing and mining introduction to data warehousing and mining
introduction to data warehousing and mining
 
Data mining & data warehousing
Data mining & data warehousingData mining & data warehousing
Data mining & data warehousing
 

Similar to Data mining and data warehousing

management information system unit 2 aktu study material quick notes easy to ...
management information system unit 2 aktu study material quick notes easy to ...management information system unit 2 aktu study material quick notes easy to ...
management information system unit 2 aktu study material quick notes easy to ...
RDX29
 
Management - mis
Management - mis Management - mis
Management - mis
SanaRiaz789
 
Management Information Systems
Management Information SystemsManagement Information Systems
Management Information Systems
Ram Dutt Shukla
 
Management Information Systems
Management  Information  SystemsManagement  Information  Systems
Management Information Systems
Ram Dutt Shukla
 

Similar to Data mining and data warehousing (20)

Needs for mis
Needs for misNeeds for mis
Needs for mis
 
Mis
MisMis
Mis
 
Characteristics of MIS and dss
Characteristics of MIS and dssCharacteristics of MIS and dss
Characteristics of MIS and dss
 
CHP-3ERP and Related Technologies.ppt
CHP-3ERP and Related Technologies.pptCHP-3ERP and Related Technologies.ppt
CHP-3ERP and Related Technologies.ppt
 
erp and related technologies
erp and related technologieserp and related technologies
erp and related technologies
 
CHP-3ERP and Related Technologies(1).ppt
CHP-3ERP and Related Technologies(1).pptCHP-3ERP and Related Technologies(1).ppt
CHP-3ERP and Related Technologies(1).ppt
 
MIS Q & A for III B.Sc C & HA
MIS Q & A for III B.Sc C & HAMIS Q & A for III B.Sc C & HA
MIS Q & A for III B.Sc C & HA
 
Business Analytics 1 Module 1.pdf
Business Analytics 1 Module 1.pdfBusiness Analytics 1 Module 1.pdf
Business Analytics 1 Module 1.pdf
 
management information system unit 2 aktu study material quick notes easy to ...
management information system unit 2 aktu study material quick notes easy to ...management information system unit 2 aktu study material quick notes easy to ...
management information system unit 2 aktu study material quick notes easy to ...
 
Exercise solution of chapter1 of datawarehouse cs614(solution of exercise)
Exercise solution of chapter1 of datawarehouse cs614(solution of exercise)Exercise solution of chapter1 of datawarehouse cs614(solution of exercise)
Exercise solution of chapter1 of datawarehouse cs614(solution of exercise)
 
ITB - UNIT 2.pdf
ITB - UNIT 2.pdfITB - UNIT 2.pdf
ITB - UNIT 2.pdf
 
Management - mis
Management - mis Management - mis
Management - mis
 
Decision Support Systems: Concept, Constructing a DSS, Executive Information ...
Decision Support Systems: Concept, Constructing a DSS, Executive Information ...Decision Support Systems: Concept, Constructing a DSS, Executive Information ...
Decision Support Systems: Concept, Constructing a DSS, Executive Information ...
 
MIS Support to Management
MIS Support to ManagementMIS Support to Management
MIS Support to Management
 
Database Systems
Database SystemsDatabase Systems
Database Systems
 
Management Information Systems
Management Information SystemsManagement Information Systems
Management Information Systems
 
Database Systems
Database SystemsDatabase Systems
Database Systems
 
Management Information Systems
Management  Information  SystemsManagement  Information  Systems
Management Information Systems
 
DSS Presentation1.pptx
DSS Presentation1.pptxDSS Presentation1.pptx
DSS Presentation1.pptx
 
Mss
MssMss
Mss
 

More from Satya P. Joshi

More from Satya P. Joshi (20)

Intergroup Conflict Management.pptx
Intergroup Conflict Management.pptxIntergroup Conflict Management.pptx
Intergroup Conflict Management.pptx
 
Training methods in human resource managment
Training methods in human resource managmentTraining methods in human resource managment
Training methods in human resource managment
 
Selection tests in human resource management
Selection tests in human resource managementSelection tests in human resource management
Selection tests in human resource management
 
Interview and it’s types - human resource managmenet
Interview and it’s types - human resource managmenetInterview and it’s types - human resource managmenet
Interview and it’s types - human resource managmenet
 
Motivation, achievement theory, goal setting theory
Motivation, achievement theory, goal setting theoryMotivation, achievement theory, goal setting theory
Motivation, achievement theory, goal setting theory
 
Characteristics, objectives & challenges of human resource manager
Characteristics, objectives & challenges of human resource managerCharacteristics, objectives & challenges of human resource manager
Characteristics, objectives & challenges of human resource manager
 
Human Resource Planning
Human Resource PlanningHuman Resource Planning
Human Resource Planning
 
Nested queries in database
Nested queries in databaseNested queries in database
Nested queries in database
 
Technology and work design in Organizational Relation
Technology and work design in Organizational RelationTechnology and work design in Organizational Relation
Technology and work design in Organizational Relation
 
Techniques of achieving google quality of service
Techniques of achieving google quality of serviceTechniques of achieving google quality of service
Techniques of achieving google quality of service
 
Overview of digital communication in HSN and Multimedia
Overview of digital communication in HSN and MultimediaOverview of digital communication in HSN and Multimedia
Overview of digital communication in HSN and Multimedia
 
Introduction to human resource management
Introduction to human resource managementIntroduction to human resource management
Introduction to human resource management
 
Security and control in Management Information System
Security and control in Management Information SystemSecurity and control in Management Information System
Security and control in Management Information System
 
Designing the supply chain network
Designing the supply chain networkDesigning the supply chain network
Designing the supply chain network
 
Introduction to Organizational Behavior and Organizational Relation
Introduction to Organizational Behavior and Organizational RelationIntroduction to Organizational Behavior and Organizational Relation
Introduction to Organizational Behavior and Organizational Relation
 
Selection tests and Reliability and Validity in HRM
Selection tests and Reliability and Validity in HRMSelection tests and Reliability and Validity in HRM
Selection tests and Reliability and Validity in HRM
 
Analog and digital signal system : digital logic
Analog and digital signal system : digital logicAnalog and digital signal system : digital logic
Analog and digital signal system : digital logic
 
Transmission media on Client server and high speed network
Transmission media on Client server and high speed networkTransmission media on Client server and high speed network
Transmission media on Client server and high speed network
 
Remote procedure call on client server computing
Remote procedure call on client server computingRemote procedure call on client server computing
Remote procedure call on client server computing
 
Physical and logical topologies in computer network and client server
Physical  and logical topologies in computer network and client serverPhysical  and logical topologies in computer network and client server
Physical and logical topologies in computer network and client server
 

Recently uploaded

Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
panagenda
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
?#DUbAI#??##{{(☎️+971_581248768%)**%*]'#abortion pills for sale in dubai@
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 

Recently uploaded (20)

"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf
 
Vector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxVector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptx
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
 
WSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering Developers
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistan
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 

Data mining and data warehousing

  • 1. Data Mining & Warehousing
  • 2. 1 ) User expectation 2 ) Systems optimization 3 ) Data structuring 4 ) Prefabricated vs. Custom warehouse 5 ) Resource balancing Challenges faced on Data Warehousing 2
  • 3. As the volume of data in a warehouse increases, warehouse management systems need to move deeper in warehouses for data analysis. The end-user in these cases demands and expects more accurate and refined results in return of processing, however that is not the case with warehouse systems.  The performance decreases with exploding data and so the efficiency of the system reduces. 1. User expectation 3
  • 4. Regressive utilization of business intelligence tools require frequent maintenance and fine tuning of whole system in order to meet users' expectations. Carefully designed and configured data analysis tool helps in providing better results for effective business development decisions. 2. Systems optimization 4
  • 5. Proper processing of data requires structuring it in a desired format so that further operations can be executed.  As the volume of data increases the task of structuring data of system eventually becomes hectic for the system manager. 3. Data structuring 5
  • 6. The varieties of warehouses available in market, create ambiguity about which type to choose or go for. Where custom warehouse saves the time of building the warehouses from various operational databases from weeks to days or even hours, prefabricated warehouses saves the time of initial configuration and installation. 4. Prefabricated vs. Custom warehouse 6
  • 7. In order to draw benefit from data warehousing, most departments inside an organization tend to access the processing capabilities of the warehouse.  This eventually reduces the performance of the system and decreases the efficiency as the stress on the system increases. Access control and security are some techniques which can be used to maintain a balance between the utilization and performance of warehouse systems. 5. Resource Balancing 7
  • 8.  Decision support systems (DSS) are a specific class of computerized information system that supports business and organizational decision -making activities.  DSS is a well integrated ,user friendly, computer based tools that combine data with various decision making models to solve semi structure and unstructured problems. Decision support system 8
  • 9.  Provide decision support for several interdependent decision.  Assist the decision maker to make decision under dynamic business conditions.  Supports a wide variety of decision making processes and style. Characteristics 9
  • 10. How a DSS works??? 10
  • 11.  Database management system  Model management system  Support tools Components of DSS 11
  • 12.  In database management ,the problem necessary to solve may come from internal and external database.  Within the organization, internal data are generated by systems such as TPS and MIS; external data come from variety of sources such as periodicals, databases, newspapers and online data services. Database Management 12
  • 13.  It stores and access models that managers use to make decisions.  Models are integral part of most decision making and are used for many tasks, such as designing a manufacturing facility, analysing the financial health of an organization, forecasting demand for a product or service, and determining the quality of a particular batch of products. Model Management Component 13
  • 14.  It consist of tools such as pull down menus, on -line help, users interface, graphical analysis and error -correction mechanisms all of which facilitate users interactions with the system.  Interfaces are an important support tools. This is because middle and top managers have neither the time nor the inclination to learn difficult and complicated procedures in order to run a system. For better the interface, the greater the chances that users will accept the system. Support Tools 14
  • 15.  Cost saving  Improve managerial effectiveness  Flexible and adaptive  Improve the effectiveness of the decision  Reduces the time and efforts in collecting and analysis of data for different sources, a large no of alternatives can be evaluated. Advantages of DSS 15
  • 16. It is also termed as Executive Support System[ESS]. It is a specialized decision support system used to assist senior executives in the decision -making process. It includes various hardware, software, data, procedures and the people. It is very user friendly in the nature. It is supported at a large extent by the graphics. Executive Information System[EIS] 16
  • 17. 17
  • 18. 1. Informational characteristics 2. User interface/orientation characteristics 3. Managerial / executive characteristics Characteristics of Executive Information System 18
  • 19. i . Flexibility and ease of use. i i . Provides the timely information with the short response time and also with the quick retrieval. i i i . Produces the correct information. i v . Produces the relevant information. v . Produces the validated information. 1. Informational characteristics 19
  • 20. i . Consists of the sophisticated self help. i i . Contains the user friendly interfaces consisting of the graphic user. i i i . Can be used from many places. i v . Offers secure reliable, confidential access along with the access procedure. v . Is very much customized. Suites the management style of the individual executives. 2. User interface/orientation characteristics 20
  • 21. i . Supports the over all vision, mission and the strategy. i i . Provides the support for the strategic management. i i i . Sometimes helps to deal with the situations that have a high degree of risk. i v . Is linked to the value added business processes. v . Supports the access to database. v i . Is very much result oriented in the nature. 3. Managerial / executive characteristics 21
  • 22. 1.Achievement of the various organizational objectives. 2.Facilitates access to the information by integrating many sources of the data. 3. Facilitates broad, aggregated perspective and the context. 4. Offers broad highly aggregated information. 5. User’s productivity is also improved to a large extent. 6. Communication capability and the quality are increased. Advantages of EIS 22
  • 23. 1 . Internal factors - accurate & reliable information, improve communications, use of historical data 2. External factors - increasing global competition, changing the business environment, government regulations. Factors affecting EIS
  • 24. DSS EIS  Used by professionals  Required for day to day operations  Deals both with semi & unstructured data  Consists only of internal information  Used by executives  Required for strategic plans and procedures  Deals only with unstructured data (which cannot be described in detail)  Consists of both internal & external information 24 Differences between DSS and EIS