Presentation is loading. Please wait.

Presentation is loading. Please wait.

ندوة الدعم المؤسسي والمعلوماتي لعمل المراكز الإستراتيجية في الحكومة

Similar presentations

Presentation on theme: "ندوة الدعم المؤسسي والمعلوماتي لعمل المراكز الإستراتيجية في الحكومة"— Presentation transcript:

1 ندوة الدعم المؤسسي والمعلوماتي لعمل المراكز الإستراتيجية في الحكومة
6-10 فبراير 2005 إعداد دكتور/ شريف عبد المجيد مازن نائب مدير مركز الدراسات وتطوير نظم المعلومات كلية الحاسبات والمعلومات جامعة القاهرة

2 مقدمة عامة

3 of Information Systems
Foundations of Information Systems in Business

4 Foundation Concepts Fundamental behavioral, technical, business, and managerial concepts about the components and roles of information systems. Example: Basic information systems concepts derived from general systems theory

5 Business Applications
The major uses of information systems for the operations, management, and competitive advantage of the E-Business enterprise. Includes electronic business, commerce, collaboration, and decision making using the Internet, intranets, and extranets.

6 Development Processes
How business professionals and information specialists plan, develop, and implement information systems to meet E-Business opportunities using several strategic planning and application development approaches

7 Management Challenges
The challenges of effectively and ethically managing E-business technologies, strategies, and security at the end user, enterprise, and global levels of a business We will not be looking at this in-depth in this course

8 Information Technologies
Major concepts, developments, and management issues in information technology Hardware, software, networks, data resource management, and Internet based technologies

9 What is an Information System?
Simple Definition It can be any organized combination of people, hardware, software, communications networks and data resources that collects, transforms, and communicates information in an organization. Hardware – physical device Software – processing instructions and procedures Communications channels – networks Stored Data – data resources

10 Diagram of a System Environment Other Systems Manufacturing Process
Input of Raw Materials Output of Finished Products Environment Other Systems Control by Management Control Signals Feedback System Boundary

11 Components of an IS Four major concepts
People, hardware, software, data and networks are the five basic resources of information systems People resources include end users, IS specialists, hardware resources consist of machines and media, software resources include both programs and procedures, data resources can include data and knowledge bases, and networks include communications media and networks

12 Components of an IS Four major concepts continued…
Data resources are transformed by information processing activities into a variety of information products for end users Information processing consists of input, processing, output, storage, and control activities

13 Information System Resources

14 Information System Resources
People Resources End Users – the people who use an information system or the information it produces. Ex: Accountants, salespeople, customers IS Specialists – the people who develop and operate information systems based on the requirements of end users. Ex: programmers, analysts, system operators

15 Information System Resources
Hardware Resources Machines, such as computers and other devices, and media, such as paper, disks Computer Systems such as the personal computer (desktop), mainframe, or laptop Computer peripherals such as keyboard, mouse, monitor, scanner, printer, disks

16 Information System Resources
Software Resources Programs – sets of operating instructions that direct and control computer hardware Procedures – sets of information processing instructions that people need

17 Information System Resources
Software Resources continued System Software – such as operating system that supports the operations of a computer system. Ex. Windows 98 Application Software – programs that direct processing for a particular use of computers by end users. Ex. Excel Procedures – operating instructions for people who will use an IS. Ex. Instructions for filling out a form.

18 Information System Resources
Data Resources Types of data Text data Image data Audio data Data Storage Databases – hold processed and organized data Knowledge bases – hold knowledge in a variety of forms such as facts, rules, and case examples of successful business practices

19 Information System Resources
Data Resources continued… Data Vs. Information Data – raw facts or observations, objective measurements of the characteristics of entities such as people, places, things and events Information – data that has been converted to a meaningful and useful context for specific end users.

20 Information System Resources
Data Resources continued… Data is subjected to a value-added process Its form is aggregated, manipulated and organized Its content is analyzed and evaluated It is placed in a proper context for a human user Called data processing or information processing

21 Information System Resources
Data Resources continued… West Charles Mann 79154 TM Shoes Monthly Sales Report for West Region Sales Rep: Charles Mann Emp No Item Qty Sold Price TM Shoes $100

22 Information System Resources
Network Resources Communication media – Twisted pair wire, coaxial cable, fiber-optic cable and microwave, cellular, and satellite technologies Network support – people and all of the hardware, software, and data technologies that directly support the operation and use of a communication network.

23 Information System Activities
Input of Data Resources Data about business transactions and other events must be captured and prepared for processing Input typically takes the form of data entry activities such as recording and editing End users typically enter data directly into a computer system or record it on some physical media such as a paper form

24 Information System Activities
Processing of Data into Information Data is subjected to processing activities such as calculating, comparing, sorting, classifying and summarizing This organizes, analyzes, and manipulated data, turning it into information The quality of data stored in an information system must be maintained by a continual process of correcting and updating activities

25 Information System Activities
Output of Information Products The goal of information systems is the production of appropriate information products for end users Examples are messages, reports, forms and graphic images which may be provided by video displays, audio responses, paper products, and multimedia

26 Information System Activities
Information Quality Information that is outdated, inaccurate, or hard to understand is not meaningful, useful, or valuable to end users Information products should have characteristics, attributes, and qualities that make the information more valuable to the end users Information has three dimensions of time, form, and content

27 Information System Activities
Information Quality continued..

28 Information System Activities
Storage of Data Resources Data and information are retained in an organized manner for later use Stored data is commonly organized into fields, records, files, and databases Name Field Payroll Record File Personnel Database

29 Information System Activities
Control of System Performance An IS should produce feedback about its input, processing, output, and usage activities This feedback must be monitored and evaluated to determine if the system is meeting performance standards Activities must be adjusted so that proper information products are produced for end users

30 Business Processes and Operations
Roles of IS in Business Support of Strategic Advantage Business Decision Making Business Processes and Operations

31 History of Information Systems
Data Processing Management Reporting Decision Support Strategic & End User Electronic Commerce - TPS Information Systems - Ad hoc Reports Computing Exec Info Sys Expert Systems SIS Business & -Internetworked E-Business &

32 The E-Business Enterprise
The use of Internet technologies to inter-network and empower business processes, electronic commerce, and enterprise communication and collaboration within a company and with its customers, suppliers, and other business stakeholders.

33 The E-Business Enterprise
E-Business enterprises rely on information technologies such as the Internet to: Reengineer and revitalize internal business processes Implement electronic commerce systems among businesses and their customers and suppliers Promote enterprise collaboration among business teams and workgroup

34 The E-Business Enterprise
Enterprise collaboration systems Involve the use of groupware tools to support communication, coordination, and collaboration among members of networked teams and workgroups Electronic Commerce The buying and selling, marketing and servicing of products, services and information over a variety of computer networks

35 The E-Business Enterprise
Types of networks The Internet Intranets – the network existing inside an enterprise Extranets – networks existing between enterprises

36 The Inter-networked Business
Manufacturing and Production Engineering & Research Accounting, Finance, and Management Suppliers and Other Business Partners Procurement, Distribution, and Logistics Advertising Sales Customer Service Consumer and Business Customers Company Boundary Intranets The Internet Extranets

37 Types of Information Systems
Transaction Processing Systems Process Control Enterprise Collaboration Operations Support Management Information Decision Executive Information Systems

38 Operations Support Systems
Role is to efficiently process business transactions, control industrial processes, support enterprise communications and collaboration, and update corporate databases Examples Transaction Processing Systems – record and process data from business transactions in one of two ways – batch process and real-time process Process Control Systems – monitor and control physical processes such petroleum refining Enterprise Collaboration Systems – enhance team and workgroup communications and productivity

39 Management Support Systems
Focus on providing information and support for effective decision making by management Examples Management Information Systems – provide information in forms of reports and displays to managers and other professionals Decision Support Systems – giver direct computer support during the decision making process Executive Information Systems – provide critical information from a wide variety of internal and external sources in an easy to use displays

40 Other Classifications
Expert Systems – provide export advice for operational chores like equipment diagnostics Knowledge Management Systems – support the creation, organization, and distribution of business knowledge to employees and managers Functional Information Systems – focus on operational and managerial applications in support of basic business functions such as accounting Strategic Information Systems – apply information technology to a firm’s products, services, or business practices to gain a competitive advantage

41 Developing Information Systems
Development Cycle

42 Managerial Challenges of IT
Information systems and their technologies must be managed to support the business strategies, business processes, and organizational structures and culture of an enterprise to increase its customer and business value.

43 Managerial Challenges of IT
Business Strategies Business Processes Business Needs Customer Relationships Business Partners Suppliers Business Customers Ethical Considerations Potential Risks? Potential Laws? Possible Responses? IS Human Resources IS Development IT Infrastructure IS Performance Organization Structure and Culture User Acceptance

44 Ethical Responsibilities
Ethics and IT Ethical Responsibilities What use of IT may be considered improper, irresponsible, or harmful to other individuals or society? How to protect yourself from computer crime? Use of Internet in the business environment?

45 The IS Function A major functional area of business that is as important to business success as the functions of accounting, finance, operations management, marketing, and human resource management An important contributor to operational efficiency, employee productivity and morale, and customer service and satisfaction A major source of information and support needed to promote effective decision making by managers and business professionals

46 The IS Function A vital ingredient in developing competitive products and services that give an organization a strategic advantage in the global marketplace A dynamic, rewarding, and challenging career opportunity for millions of men and women A key component of the resources, infrastructure, and capabilities of today’s e-business enterprises

47 أنواع القرارات Unstructured Decisions Structured Decisions
Non-routine decisions; there is no agreed-upon procedure for making these decisions. Structured Decisions Decisions that are routine, repetitive, and have a definite procedure for handling them. Semi-Structured Decisions Decisions where only part of the problem has a clear-cut answer provided by an accepted procedure.

48 أنواع نظم المعلومات Transaction Processing Systems (TPS)
نظم معلومات تشغيل العمليات Knowledge Work Systems (KWS) نظم المعرفة Office Automation Systems (OAS) نظم ميكنة المكتب Management Information Systems (MIS) نظم المعلومات الإدارية Decision Support Systems (DSS) نظم دعم اتخاذ القرار Executive Support Systems (ESS) نظم دعم المستوى التنفيذي Expert Systems (ES) Replicates decision making process النظم الخبيرة

49 Types of Information Systems

50 مستويات عملية اتخاذ القرار
Strategic Decision Making Determines the long-term objectives, resources, and policies of an organization. Decision Making for Management Control Concerned with how efficiently or effectively resources are utilized and how well operational units are performing. Knowledge-Level Decision Making Evaluates new ideas for products, services, ways to communicate new knowledge, and ways to distribute information throughout the organization. Decision Making for Operational Control Decides how to carry out the specific tasks set forth by strategic and middle management and establishes criteria for completion and resource allocation.

51 نظم معلومات تشغيل العمليات Transaction Processing Systems
Operational level Inputs: Transactions, Events Processing: Updating Outputs: Detailed reports Users: Operations personnel Example: Accounts payable, Payroll

52 نظم المعرفة Knowledge Systems
Knowledge level Inputs: Design specs Processing: Modeling Outputs: Designs, Graphics Users: Technical staff (knowledge workers) Example: Engineering workstation

53 نظم ميكنة المكتب Office Automation Systems
Toward a “paperless” office Redesign of work flow Integrated software Ergonomic design Bright, cheerful work space Users: data (clerical) workers Example: document imaging system

54 نظم المعلومات الإدارية Management Information Systems
Management level Supports structured & semi-structured decisions. Inputs: high volume data (e.g. from TPS) Processing: simple models Outputs: summary reports Users: middle managers Example: annual budgeting

55 نظم دعم اتخاذ القرار Decision Support Systems
Management level Supports semi-structured, unique, rapidly changing, not easily specified decisions. Inputs: Data from various sources (e.g., MIS, TPS, KWS) Processing: Interactive Outputs: Decision analysis Users: Professionals, staff Example: Contract Cost Analysis

56 نظم دعم المستوى التنفيذي Executive Support Systems
Strategic level Supports unstructured decisions. Inputs: Aggregate data (external, MIS, DSS) Processing: Interactive Outputs: Projections Users: Senior managers Example: 5 Year operating plan

57 العلاقة بين نظم المعلومات المختلفة
ESS MIS DSS KWS/ OAS TPS TPS is a major producer of information for other systems


59 التكامل بين كل من نظم تشغيل العمليات ونظم المعلومات الإدارية ونظم دعم اتخاذ القرار
In many organizations they are integrated through a common database Separation of DSS transactions in the database from TPS and MIS transactions may be important for performance reasons

60 مراحل عملية اتخاذ القرار
Intelligence Collects information to identify problems occurring in the organization. Design Designs possible alternative solutions to a problem. Choice Selects among the various solution alternatives Implementation Puts the decision into effect and reports on the progress of the solution.

61 The Decision Making Process

62 Information Requirement and IS
Stage of Decision Making Information Requirement Example IS Intelligence Exception reporting MIS Design Simulation prototype DSS, KWS Choice “What-if” simulation DSS; large models Implementation Graphics, charts PC and mainframe decision aids

63 مهام نظم دعم اتخاذ القرار
Assist management decision making by combining data, sophisticated analytical tools and user friendly S/W into a single powerful system. Focus on a specific decision or classes of decisions (e.g. evaluating, predicting), whereas MIS focus on routine, general control of the organization.

64 أنواع نظم دعم اتخاذ القرار
Model-Driven DSS (early DSS, 70s, 80s~) Stand-alone system based on a strong theory/model to perform “what-if” and other kinds of analysis. Data-Driven DSS Allow users to extract and analyze useful info buried in large databases. Data mining: Technology for finding hidden patterns and relationships in large databases and inferring rules from them to predict future behavior; it provides insights into corporate data.

65 بعض الأمثلة لنظم دعم اتخاذ القرار
Geographic Information Systems (GIS) A special DSS with S/W that can analyze and display data for planning and decision making using digitized maps. Assemble, store and display geographically referenced info, tying data to points, lines, and areas on a map. Can be used to calculate emergency response times to natural disasters; help banks identify the best locations for installing ATM terminals.

66 بعض الأمثلة لنظم دعم اتخاذ القرار (2)
Customer Decision Support System (CDSS) Recently being developed based on the Web. System to support the decision-making process of an existing or potential customers. Developed to attract customers by providing information and tools to assist their decision making as they select products and services.

67 قدرات نظم دعم اتخاذ القرار
Supports Problem solving phases Different decision frequencies Merge with another company? How many widgets should I order? low high Frequency

68 قدرات نظم دعم اتخاذ القرار (2)
Highly structured problems Straightforward problems, requiring known facts and relationships. Semi-structured or unstructured problems Complex problems wherein relationships among data are not always clear, the data may be in a variety of formats, and are often difficult to manipulate or obtain.

69 خصائص نظم دعم اتخاذ القرار
Handles large amounts of data from different sources Provides report and presentation flexibility Offers both textual and graphical orientation Supports drill down analysis Performs complex, sophisticated analysis and comparisons using advanced software packages Supports optimization, satisfying, and heuristic approaches

70 خصائص نظم دعم اتخاذ القرار (2)
Performs different types of analysis “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

71 Solution Types Optimization model Satisfying model Heuristics
Finding the best solution. Satisfying model Finding a good - but not necessarily the best - solution to a problem. Heuristics Commonly accepted guidelines or procedures that usually find a good solution.

72 Problem Solving Factors
Multiple decision objectives Increased alternatives Increased competition The need for creativity Social and political actions International aspects Technology Time compression

73 Goal Seeking Example You know the desired result
You want to know the required input(s) Example: Microsoft Excel’s “Goal Seek” and “Solver” functions

74 Excel demo

75 نظم دعم اتخاذ القرار على الإنترنت
Web-based decision support systems DSS SW provides business intelligence through web browser clients that access databases either through the Internet or a corporate intranet.

76 مكونات نظم دعم اتخاذ القرار
Model Management Software (MMS) Coordinates the use of models in the DSS. Model Base Provides decision makers with access to a variety of models. Dialogue Manager Allows decision makers to easily access and manipulate the DSS.

77 Database Model Base DBMS MMS External Databases
Access to the Internet, Networks, and other Computer Systems External Database Access Dialogue Manager

78 Model Base Model Base Models
Provides decision makers with access to a variety of models and assists them in decision making. Models Financial models Statistical Analysis models Graphical models Project Management models

79 Advantages and Disadvantages of Modeling
Less expensive than custom approaches or real systems. Faster to construct than real systems. Less risky than real systems. Provides learning experience (trial and error). Future projections are possible. Can test assumptions. Disadvantages Assumptions about reality may be incorrect. Accuracy of predications often unreliable. Requires abstract thinking.

80 Group Decision Support System
Group Decision Support System (GDSS) Contains most of the elements of DSS plus software to provide effective support in group decision-making settings.

81 External database access
Databases Model base GDSS processor GDSS software External databases Access to the internet and corporate intranet, networks, and other computer system Dialogue manager External database access Users

82 Executive Support System (ESS)
Characteristics A specialized DSS that includes all the hardware, software, data, procedures, and people used to assist senior-level executives within the organization. Board of directors President Function area vice presidents Function area managers

83 Characteristics of ESSs
Tailored to individual executives Easy to use Drill down capabilities Support the need for external data Help with situations with high degree of uncertainty Futures orientation (predictions, forecasting) Linked with value-added business processes

84 Capabilities of an ESS Support for :- Defining overall vision
Strategic planning Strategic organizing and staffing Strategic control Crisis management

85 Constructing, Implementing, and Evaluating a Decision Support System
DSS Development DSS Implementation DSS Evaluation

86 Developing a specific DSS
Planning for DSS BSP approaches CSF approaches Developing a specific DSS Step 1. Decide on development methodology Step 2. Requirements analysis Step 3. Logical design Step 4. Construction Step 5. Implementation

87 Make versus Buy Alternatives Buy shrink-wrapped
Customize a shrink-wrapped Build from specialized tools / generators Build “from scratch”

88 Step 1. DSS Development Approaches
SDLC Evolutionary prototyping Throwaway prototyping End user development Strengths and weaknesses

89 The System Development Life Cycle (SDLC) Approach & DSS
Inappropriate for most DSS. Users and Managers may not understand their information and modeling needs. Use in conjunction with Throwaway prototyping.

90 Prototyping Process of building a "quick and dirty" version of an Information System Evolutionary Prototyping

91 Evolutionary Steps 1. Identify user's information and operating requirements in a "quick and dirty" manner. 2. Develop a working prototype that performs only the most important function 3. Test and evaluate (By User and Builder). 4. Redefine information needs and improve the system.

92 The Primary Features of Prototyping
1. Learning is explicitly integrated into the design process 2. Short intervals between iterations 3. User involvement is very important (Joint Application Development (JAD) method) 4. Initial prototype must be low cost 5. Prototyping essentially bypasses the life-cycle stage of information requirements definition

93 Advantages of Prototyping
Short development time Short user reaction time (feedback from user) Improved users' understanding of the system, its information needs, and its capabilities. Low cost Disadvantages and Limitations Gains might be lost through cycles

94 User-Developed DSS advantages
End-user development means the development and use of computer-based information systems by people outside the formal IS areas. 1. Short delivery time 2. Eliminate extensive and formal user requirements specifications 3. Reduce some DSS implementation problems 4. Low cost

95 User-Developed DSS Risks
1. Poor Quality 2. Quality Risks Substandard or inappropriate tools and facilities Development process risks Data management risks 3. Increased Security Risks 4. Problems from Lack of Documentation 5. Problems from Maintenance Procedures

96 Issues in reducing End-User Computing Risks
Error detection Use of auditing techniques Training and Support Determine the proper amount of controls Investigate the reasons for the errors Solutions

97 Step 2. Requirements Analysis
Goal: To understand how DM conceptualizes, analyses, and communicates problems. Direct methods Interviews, group meetings, JAD Indirect methods Observation, temporary job assignments, questionnaires, document review, software review Addressing compiled knowledge Protocol analysis Card sorting, multidimensional scaling

98 Categorization of DSS Software
Specific DSS The application doing the decision support. DSS generator “Package” that provides capabilities to build Specific DSS special purpose languages, such as IFPS DSS tools tools that facilitate development of a specific DSS or DSS generator 3 GLs – 4GLs Now all with Web Hooks and easy GUI interfaces

99 Selection of DSS Development Tools
Determine & contact key participants Elicit requirements / functionality Compose requirements into a RFP Distribute RFPs to potential vendors Collect and summarize RFP data Select RFP short list Set short list interviews and demos; references Select Vendor Negotiate contract

100 Complexity of the Software Selection Process
1. DSS information requirement and outputs are not completely known 2. Hundreds of software packages 3. Software packages evolve very rapidly 4. Frequent price changes 5. Several people involved

101 6. One language for several DSS? Tool requirements may change
7. Dozens of criteria, some intangible, some conflict 8. Technical, functional, end-user, and managerial issues 9. Published evaluations are subjective and superficial 10.Trade off between open and closed environments

102 Step 5. Implementation as Change
From development to production technology acquisition port to production platform database conversion system conversion strategy user access, training, & ongoing support documentation & maintenance From implementation to institutionalization existence does not guarantee use use does not guarantee success

103 Implementation CSFs User involvement Management commitment
Design quality Performance level Project management System institutionalization

104 Evaluating DSS Success
Technical quality Response time Throughput Reliability Data integrity Requirements coverage Does what it’s supposed to do Use & usability Number of users Frequency of use User-friendliness Accessibility Economic benefits Cost of decision Benefits of improved decision-making the problems of measurement and quantification

105 Benefits of DSS Usage More effective decision making
faster assimilation of information and/or identification of problems exploration of more alternatives visual comparison of alternative consequences/outcomes environment of collaboration More efficient decision making reduce the length of the decision cycle reduce the cost of the decision

106 Benefits of DSS Usage (2)
Better communication & collaboration among decision makers shared information and shared model implicit assumptions made explicit Improved learning process for users offset cognitive limitations of decision makers; focus on higher-level thinking provide environment for utilizing knowledge provide environment for acquiring experience

107 Drawbacks to DSS Usage overemphasize on (rational) decision making
versus social, intuitive, and personalized approaches to reaching resolution assumption of relevance DSS must address most relevant aspects of decision-making

108 Drawbacks to DSS Usage Unintended transfer of power
from decision-maker to DSS between decision makers Obscuring responsibility DSS as independent entity that must be “right” tendency to trust DSS and its designers

109 E-Business Decision Support

110 Decisions in the E-Business
Strategic Management Tactical Operational Decisions Information Decision Characteristics Unstructured Semi-structured Structured To succeed in E-Business and E-Commerce, companies need information systems that can support the diverse information and decision making needs of business professionals. The type of information required by decision makers in a company is directly related to the level of management and the amount of structure in the decision situation. Strategic Planning and Control. Top executives develop overall organizational goals, strategies, policies, and objectives through long-range strategic planning. They also monitor the strategic performance of the organization and its overall direction. As a result, they are typically involved in making unstructured decisions; that is decisions where decision procedures to be followed cannot be specified in advance. Tactical Planning and Control. Middle managers develop short- and medium-range plans and budgets and specify the policies, procedures, and objectives for subunits of the organization. They also acquire and allocate resources and monitor performance of organizational subunits at the department, division, and other workgroup levels. Hence, these managers make more semi-structured decisions in which only some of the decision procedures can be specified in advance. Operational Planning and Control. Supervisory managers develop short-term planning devices such as production schedules. Supervisors are front-line managers who direct the actions of non-management employees. Their IS needs are often linked to the processing, monitoring, and evaluating of physical products. Thus, their decisions are more structured; that is to say, they can be specified in advance.

111 MIS Reports Major Management Information Systems Reports
Periodic Scheduled Reports Exception Reports Demand Reports and Responses Push Reports Major Management Information Systems Reports The Management Information System concept, also called information reporting systems, was the original type of management support system. MIS produce information products that support many of the day-to-day decision-making needs of the organization. Three major reporting alternatives include: Periodic Scheduled Reports. This traditional form of providing information to managers uses a prespecified format designed to provide managers with information on a regular basis. Typical examples include weekly sales analysis reports and monthly financial statements. Exception Reports. These are generated when a specific set of conditions occur. The IS can be designed to produce exception reports when some process exceeds given parameters and requires management action. Exception reports reduce information overload. They also promote management by exception -- intervening only when decisions need to be made. Demand Reports and Responses. These provide information whenever a manager demands it. For example, DBMS query languages and report generators allow managers at online workstations to get immediate responses or reports to their requests for information. Push Reporting. Many companies are using webcasting software to selectively broadcast reports and other information to the networked PCs of managers and specialists over their corporate intranets. In this manner, information is pushed to a manager’s networked workstation.

112 Online Analytical Processing
OLAP Server Multi- dimensional database Corporate Databases Client PC Web-enabled OLAP Software Data is retrieved from corporate databases and staged in an OLAP multi-dimensional Operational DB Data Marts Data Warehouse Online Analytical Processing (OLAP) is a capability of management, decision support, and executive information systems that enables managers and analysts to interactively examine and manipulate large amounts of detailed and consolidated data from many perspectives. Basic analytical operations include: Consolidation. This involves the aggregation of data. It can be simple roll-ups or complex groupings involving interrelated data. For example, sales offices can be rolled up to districts and districts rolled up to regions. Drill-Down. OLAP can go in the reverse direction and automatically display detailed data that comprises consolidated data. For example, the sales by individual products or sales reps that make up a region's sales can be accessed easily. Slicing and Dicing. This refers to the ability to look at the database from different viewpoints. For example, one slice of a database might show all sales of a product within regions. Another slice might show all sales by sales channel. By allowing rapid alternative perspectives, slicing and dicing allows managers to isolate the information of interest for decision making.

113 Decision Support Systems
What If-Analysis Sensitivity Analysis Goal-Seeking Analysis Optimization Analysis Important Decision Support Systems Analytical Models Decision support systems (DSS) are computer-based systems that provide managers and business professionals interactive information support for semi-structured and unstructured decisions. Unlike management information systems, DSS rely on model bases. A model base is a software component that consists of models used in computational and analytical routines that mathematically express relationships between variables. There are various types of DSS analytical model bases. These include: What-If Analysis. An end user makes changes to variables, or relationships among variables, and observes the resulting change in the value of other variables. Sensitivity Analysis. A special type of what-if analysis in which the value of only one variable is changed repeatedly, and the resulting changes on other variables are observed. Goal-Seeking Analysis. Instead of observing how changes in a variable affect other variables, goal-seeking analysis sets a target value for a variable, and then repeatedly changes other variables until the target value is achieved. Optimization analysis. A more complex goal-seeking model. Instead of setting a specific target value for a variable, the goal is to find the optimum value for one or more target variables, given certain constraints.

114 Enterprise Information Portals & DSS
Enterprise Information Portal Gateway Enterprise Information Portal User Interface Search Agents OLAP Data Mining Knowledge Management Database Management Functions Mart Other Business Applications Operational Database Analytical Base DSS What-If Models Sensitivity Models Goal-Seeking Models Optimization Models Internet Intranet Extranet Cross-platform integration is one of the main objectives of today’s E-Business. As shown in the figure, newer DSS packages not only are capable of running under different computer platforms, but can be integrated with corporate data resources, including operational databases, data marts, and data warehouses. These packages are no longer limited to numeric input and response, but can use data visualization systems to represent complex data using interactive three dimensional graphical forms. This in turns helps users discover patterns and links between decision variables quicker and easier. As we stated earlier, the objective of today’s E-Business is to provide information to anyone that needs it, whenever, and wherever they are. More and more companies are developing Enterprise Information Portals to provide web-enabled access to information. When deployed successfully, this portal provides a universal interface to both corporate knowledge and decision-making tools as well as a wealth of other tools.

115 Artificial Intelligence Applications
Cognitive Science Applications Artificial Intelligence Robotics Natural Interface Expert Systems Fuzzy Logic Genetic Algorithms Neural Networks Visual Perceptions Locomotion Navigation Tactility Natural Language Speech Recognition Multisensory Interface Virtual Reality Artificial Intelligence (AI) is a science and technology based on disciplines such as computer science, biology, psychology, linguistics, mathematics, and engineering. AI works to develop computer functions normally associated with human intelligence. Its goal is to develop computers that can think, see, hear, walk, talk, and even feel. The major application areas of AI can be grouped into three categories: Cognitive Science. Much of AI development is based upon research in human information processing, which focuses on understanding how the human brain works and how humans think and learn. Major applications in this area include: expert systems, learning systems, fuzzy logic, genetic algorithms, neural networks, and intelligent agents. Robotics. Robotics is concerned with deploying computers in ways that duplicate the actions (and even the appearance) of humans. Areas of development include visual perception, tactility, dexterity, locomotion, and navigation. Natural Interface. AI developers hope to make the human-computer interface as natural as possible. Natural language programming, speech recognition, multisensory interfaces, and virtual reality are all areas of development.

116 AI Application Areas in Business
Neural Networks Fuzzy Logic Systems Virtual Reality Expert Systems AI Application Areas in Business Intelligent Agents Genetic Algorithms There are numerous AI application areas in business. These include: Neural Networks. Computing systems modeled after the brain’s mesh-like network of interconnected processing elements, called neurons. The interconnected processors in a neural network operate in parallel and interact dynamically. This enables the network to learn to recognize patterns and relationships in the data it processes. For example, a neural network can be used to learn which credit characteristics result in good or bad loans. Fuzzy Logic. A method of reasoning that allows for approximate values and inferences. This enables fuzzy systems to process incomplete data and quickly provide approximate, but acceptable solutions. Fuzzy systems are used in fuzzy process controller microchips that are incorporated in many Japanese appliances. Genetic Algorithms. Uses Darwinian randomizing and other mathematical functions to simulate an evolutionary process that yields increasingly better solutions to a problem. They are especially useful for situations in which thousands of solutions are possible and must be evaluated to produce an optimal solution. Virtual Reality. Is a computer-simulated reality that uses such devices as tracking headsets and data gloves to create virtual worlds that can be experienced through sight, sound, and touch. Current applications of virtual reality include computer-aided design, medical diagnostics, flight simulation, and 3-D video arcade games. On the next two slides we will focus on two very popular AI business areas.

117 Components of Expert Systems
The Expert System Knowledge Base User Workstation Expert Advice Interface Programs Inference Engine Program Expert System Development Engineering Acquisition Expert and/or Knowledge Engineer An Expert System (ES) is a knowledge-based information system that uses its knowledge about a specific, complex application area to act as an expert consultant to end users. The components of an ES include: Knowledge Base. A knowledge base contains knowledge needed to implement the task. There are two basic types of knowledge: Factual knowledge. Facts, or descriptive information, about a specific subject area. Heuristics. A rule of thumb for applying facts and/or making inferences, usually expressed as rules. Inference Engine. An inference engine provides the ES with its reasoning capabilities. The inference engine processes the knowledge related to a specific problem. It then makes associations and inferences resulting in recommended courses of action. User Interface. This is the means for user interactions. To create an expert system a knowledge engineer acquires the task knowledge from the human expert using knowledge acquisition tools. Using an expert system shell, which contains the user interface and inference engine software modules, the KE then encodes the knowledge into the knowledge base. A reiterative approach is used to test and refine the expert system's knowledge base until it is deemed complete.

118 Expert System Applications
Decision Management Diagnostic/Troubleshooting Maintenance/Scheduling Design/Configuration Selection/Classification Major Application Categories of Expert Systems Process Monitoring/Control Expert Systems can be used to accomplish many business tasks: Decision Management. This includes systems that appraise situations or consider alternatives and make recommendations based on criteria supplied during the discovery process. Examples include loan portfolio analysis, employee evaluation, insurance underwriting, demographic forecasts. Diagnostic/Troubleshooting. This is the use of systems that infer underlying causes from reported symptoms and history. Examples include equipment calibration, help desk operations, software debugging, medical diagnosis. Maintenance/Scheduling. This includes systems that prioritize and schedule limited or time-critical resources. Examples include maintenance scheduling, production scheduling, education scheduling, project management. Design/Configuration. This is the use of systems that help configure equipment components, given existing constraints that must be taken into account. Examples include computer option installation, manufacturability studies, communications networks, optimum assembly plan. Selection/Classification. These are systems that help users choose products or processes from among large or complex sets of alternatives. Examples include material selection, delinquent account identification, information classification, suspect identification. Process Monitoring/Control. This includes systems that monitor and control procedures or processes. Examples include machine control (including robotics), inventory control, production monitoring, chemical testing. Expert systems provide a business with faster, consistent expertise. They also help preserve organizational knowledge. However, they are not without limitations. ES are not suitable for every problem situation. They excel only in solving specific types of problems in a limited domain of knowledge. They fail to solve problems requiring a broad knowledge base. Expert Systems are also difficult and costly to develop and maintain.

119 Summary DSS in business are changing. The growth of corporate intranets, extranets, and other web technologies have increased the demand for a variety of personalized, proactive, web-enabled analytical techniques to support DSS. Information systems must support a variety of management decision-making levels and decisions. These include the three levels of management activity: strategic, tactical, and operational.

120 Summary (cont) Online analytical processing is used to analyze complex relationships among large amounts of data stored in multidimensional databases. Data mining analyzes large stores of historical data contained in data warehouses. Decision support systems are interactive computer-based information systems that use DSS software and a model base to provide information to support semi-structured and unstructured decision making.

121 Summary (cont) The major application domains in artificial intelligence include a variety of applications in cognitive sciences, robotics, and natural interfaces. Major AI application areas include: Neural Networks Fuzzy Logic Genetic Algorithms Virtual Reality Intelligent Agents

122 References Efraim Turban & Jay E. Aronson
“ Decision Support Systems and Intelligent Systems “ Prentice Hall, Upper Saddle River, NJ (1998)

Download ppt "ندوة الدعم المؤسسي والمعلوماتي لعمل المراكز الإستراتيجية في الحكومة"

Similar presentations

Ads by Google