3 of Information Systems Foundationsof Information Systemsin Business
4 Foundation ConceptsFundamental 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 businessWe will not be looking at this in-depth in this course
8 Information Technologies Major concepts, developments, and management issues in information technologyHardware, software, networks, data resource management, and Internet based technologies
9 What is an Information System? Simple DefinitionIt 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 deviceSoftware – processing instructions and proceduresCommunications channels – networksStored Data – data resources
10 Diagram of a System Environment Other Systems Manufacturing Process Input ofRaw MaterialsOutput ofFinished ProductsEnvironmentOther SystemsControl byManagementControlSignalsFeedbackSystem Boundary
11 Components of an IS Four major concepts People, hardware, software, data and networks are the five basic resources of information systemsPeople 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 usersInformation processing consists of input, processing, output, storage, and control activities
14 Information System Resources People ResourcesEnd Users – the people who use an information system or the information it produces. Ex: Accountants, salespeople, customersIS 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 ResourcesMachines, such as computers and other devices, and media, such as paper, disksComputer Systems such as the personal computer (desktop), mainframe, or laptopComputer peripherals such as keyboard, mouse, monitor, scanner, printer, disks
16 Information System Resources Software ResourcesPrograms – sets of operating instructions that direct and control computer hardwareProcedures – sets of information processing instructions that people need
17 Information System Resources Software Resources continuedSystem Software – such as operating system that supports the operations of a computer system. Ex. Windows 98Application Software – programs that direct processing for a particular use of computers by end users. Ex. ExcelProcedures – operating instructions for people who will use an IS. Ex. Instructions for filling out a form.
18 Information System Resources Data ResourcesTypes of dataText dataImage dataAudio dataData StorageDatabases – hold processed and organized dataKnowledge 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. InformationData – raw facts or observations, objective measurements of the characteristics of entities such as people, places, things and eventsInformation – 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 processIts form is aggregated, manipulated and organizedIts content is analyzed and evaluatedIt is placed in a proper context for a human userCalled data processing or information processing
21 Information System Resources Data Resources continued…West Charles Mann79154 TM ShoesMonthly Sales Reportfor West RegionSales Rep: Charles MannEmp NoItem Qty Sold PriceTM Shoes $100
22 Information System Resources Network ResourcesCommunication media – Twisted pair wire, coaxial cable, fiber-optic cable and microwave, cellular, and satellite technologiesNetwork 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 ResourcesData about business transactions and other events must be captured and prepared for processingInput typically takes the form of data entry activities such as recording and editingEnd 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 InformationData is subjected to processing activities such as calculating, comparing, sorting, classifying and summarizingThis organizes, analyzes, and manipulated data, turning it into informationThe 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 ProductsThe goal of information systems is the production of appropriate information products for end usersExamples 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 QualityInformation that is outdated, inaccurate, or hard to understand is not meaningful, useful, or valuable to end usersInformation products should have characteristics, attributes, and qualities that make the information more valuable to the end usersInformation has three dimensions of time, form, and content
27 Information System Activities Information Quality continued..
28 Information System Activities Storage of Data ResourcesData and information are retained in an organized manner for later useStored data is commonly organized into fields, records, files, and databasesNameFieldPayrollRecordFilePersonnelDatabase
29 Information System Activities Control of System PerformanceAn IS should produce feedback about its input, processing, output, and usage activitiesThis feedback must be monitored and evaluated to determine if the system is meeting performance standardsActivities must be adjusted so that proper information products are produced for end users
30 Business Processes and Operations Roles of IS in BusinessSupport ofStrategicAdvantageBusinessDecision MakingBusiness Processes and Operations
31 History of Information Systems DataProcessingManagementReportingDecisionSupportStrategic &End UserElectronicCommerce- TPSInformationSystems- Ad hocReportsComputingExec Info SysExpert SystemsSISBusiness &-InternetworkedE-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 processesImplement electronic commerce systems among businesses and their customers and suppliersPromote enterprise collaboration among business teams and workgroup
34 The E-Business Enterprise Enterprise collaboration systemsInvolve the use of groupware tools to support communication, coordination, and collaboration among members of networked teams and workgroupsElectronic CommerceThe buying and selling, marketing and servicing of products, services and information over a variety of computer networks
35 The E-Business Enterprise Types of networksThe InternetIntranets – the network existing inside an enterpriseExtranets – networks existing between enterprises
36 The Inter-networked Business ManufacturingandProductionEngineering &ResearchAccounting,Finance, andManagementSuppliers and Other Business PartnersProcurement, Distribution, and LogisticsAdvertising Sales Customer ServiceConsumer and Business CustomersCompanyBoundaryIntranetsThe InternetExtranets
37 Types of Information Systems TransactionProcessingSystemsProcessControlEnterpriseCollaborationOperationsSupportManagementInformationDecisionExecutiveInformation Systems
38 Operations Support Systems Role is to efficiently process business transactions, control industrial processes, support enterprise communications and collaboration, and update corporate databasesExamplesTransaction Processing Systems – record and process data from business transactions in one of two ways – batch process and real-time processProcess Control Systems – monitor and control physical processes such petroleum refiningEnterprise Collaboration Systems – enhance team and workgroup communications and productivity
39 Management Support Systems Focus on providing information and support for effective decision making by managementExamplesManagement Information Systems – provide information in forms of reports and displays to managers and other professionalsDecision Support Systems – giver direct computer support during the decision making processExecutive 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 diagnosticsKnowledge Management Systems – support the creation, organization, and distribution of business knowledge to employees and managersFunctional Information Systems – focus on operational and managerial applications in support of basic business functions such as accountingStrategic 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 StrategiesBusiness ProcessesBusiness NeedsCustomer RelationshipsBusiness PartnersSuppliersBusiness CustomersEthical ConsiderationsPotential Risks?Potential Laws?Possible Responses?IS Human ResourcesIS DevelopmentIT InfrastructureIS PerformanceOrganization Structureand CultureUser Acceptance
44 Ethical Responsibilities Ethics and ITEthical ResponsibilitiesWhat 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 FunctionA major functional area of business that is as important to business success as the functions of accounting, finance, operations management, marketing, and human resource managementAn important contributor to operational efficiency, employee productivity and morale, and customer service and satisfactionA major source of information and support needed to promote effective decision making by managers and business professionals
46 The IS FunctionA vital ingredient in developing competitive products and services that give an organization a strategic advantage in the global marketplaceA dynamic, rewarding, and challenging career opportunity for millions of men and womenA 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 DecisionsDecisions that are routine, repetitive, and have a definite procedure for handling them.Semi-Structured DecisionsDecisions 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 العملياتKnowledge Work Systems (KWS)نظم المعرفةOffice Automation Systems (OAS)نظم ميكنة المكتبManagement Information Systems (MIS)نظم المعلومات الإداريةDecision Support Systems (DSS)نظم دعم اتخاذ القرارExecutive Support Systems (ESS)نظم دعم المستوى التنفيذيExpert Systems (ES)Replicates decision making processالنظم الخبيرة
50 مستويات عملية اتخاذ القرار Strategic Decision MakingDetermines the long-term objectives, resources, and policies of an organization.Decision Making for Management ControlConcerned with how efficiently or effectively resources are utilized and how well operational units are performing.Knowledge-Level Decision MakingEvaluates new ideas for products, services, ways to communicate new knowledge, and ways to distribute information throughout the organization.Decision Making for Operational ControlDecides 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 levelInputs: Transactions, EventsProcessing: UpdatingOutputs: Detailed reportsUsers: Operations personnelExample: Accounts payable, Payroll
52 نظم المعرفة Knowledge Systems Knowledge levelInputs: Design specsProcessing: ModelingOutputs: Designs, GraphicsUsers: Technical staff (knowledge workers)Example: Engineering workstation
53 نظم ميكنة المكتب Office Automation Systems Toward a “paperless” officeRedesign of work flowIntegrated softwareErgonomic designBright, cheerful work spaceUsers: data (clerical) workersExample: document imaging system
54 نظم المعلومات الإدارية Management Information Systems Management levelSupports structured & semi-structured decisions.Inputs: high volume data (e.g. from TPS)Processing: simple modelsOutputs: summary reportsUsers: middle managersExample: annual budgeting
55 نظم دعم اتخاذ القرار Decision Support Systems Management levelSupports semi-structured, unique, rapidly changing, not easily specified decisions.Inputs: Data from various sources (e.g., MIS, TPS, KWS)Processing: InteractiveOutputs: Decision analysisUsers: Professionals, staffExample: Contract Cost Analysis
56 نظم دعم المستوى التنفيذي Executive Support Systems Strategic levelSupports unstructured decisions.Inputs: Aggregate data (external, MIS, DSS)Processing: InteractiveOutputs: ProjectionsUsers: Senior managersExample:5 Year operating plan
57 العلاقة بين نظم المعلومات المختلفة ESSMISDSSKWS/OASTPSTPS 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 databaseSeparation of DSS transactions in the database from TPS and MIS transactions may be important for performance reasons
60 مراحل عملية اتخاذ القرار IntelligenceCollects information to identify problems occurring in the organization.DesignDesigns possible alternative solutions to a problem.ChoiceSelects among the various solution alternativesImplementationPuts the decision into effect and reports on the progress of the solution.
62 Information Requirement and IS Stage of Decision Making Information Requirement Example ISIntelligence Exception reporting MISDesign Simulation prototype DSS, KWSChoice “What-if” simulation DSS;large modelsImplementation Graphics, charts PC andmainframedecision 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 DSSAllow 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 SupportsProblem solving phasesDifferent decision frequenciesMerge with another company?How many widgets should I order?lowhighFrequency
68 قدرات نظم دعم اتخاذ القرار (2) Highly structured problemsStraightforward problems, requiring known facts and relationships.Semi-structured or unstructured problemsComplex 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 sourcesProvides report and presentation flexibilityOffers both textual and graphical orientationSupports drill down analysisPerforms complex, sophisticated analysis and comparisons using advanced software packagesSupports optimization, satisfying, and heuristic approaches
70 خصائص نظم دعم اتخاذ القرار (2) Performs different types of analysis“What-if” analysisMakes hypothetical changes to problem and observes impact on the resultsSimulationDuplicates features of a real systemGoal-seeking analysisDetermines problem data required for a given result
71 Solution Types Optimization model Satisfying model Heuristics Finding the best solution.Satisfying modelFinding a good - but not necessarily the best - solution to a problem.HeuristicsCommonly accepted guidelines or procedures that usually find a good solution.
72 Problem Solving Factors Multiple decision objectivesIncreased alternativesIncreased competitionThe need for creativitySocial and political actionsInternational aspectsTechnologyTime 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
75 نظم دعم اتخاذ القرار على الإنترنت Web-based decision support systemsDSS 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 BaseProvides decision makers with access to a variety of models.Dialogue ManagerAllows 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 SystemsExternal Database AccessDialogue Manager
78 Model Base Model Base Models Provides decision makers with access to a variety of models and assists them in decision making.ModelsFinancial modelsStatistical Analysis modelsGraphical modelsProject 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.DisadvantagesAssumptions 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 DatabasesModel baseGDSS processorGDSS softwareExternal databasesAccess to the internet and corporate intranet, networks, and other computer systemDialogue managerExternal database accessUsers
82 Executive Support System (ESS) CharacteristicsA specialized DSS that includes all the hardware, software, data, procedures, and people used to assist senior-level executives within the organization.Board of directorsPresidentFunction area vice presidentsFunction area managers
83 Characteristics of ESSs Tailored to individual executivesEasy to useDrill down capabilitiesSupport the need for external dataHelp with situations with high degree of uncertaintyFutures orientation (predictions, forecasting)Linked with value-added business processes
84 Capabilities of an ESS Support for :- Defining overall vision Strategic planningStrategic organizing and staffingStrategic controlCrisis management
85 Constructing, Implementing, and Evaluating a Decision Support System DSS DevelopmentDSS ImplementationDSS Evaluation
86 Developing a specific DSS Planning for DSSBSP approachesCSF approachesDeveloping a specific DSSStep 1. Decide on development methodologyStep 2. Requirements analysisStep 3. Logical designStep 4. ConstructionStep 5. Implementation
87 Make versus Buy Alternatives Buy shrink-wrapped Customize a shrink-wrappedBuild from specialized tools / generatorsBuild “from scratch”
88 Step 1. DSS Development Approaches SDLCEvolutionary prototypingThrowaway prototypingEnd user developmentStrengths 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 PrototypingProcess of building a "quick and dirty" version of an Information SystemEvolutionary Prototyping
91 Evolutionary Steps1. Identify user's information and operating requirements in a "quick and dirty" manner.2. Develop a working prototype that performs only the most important function3. 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 process2. Short intervals between iterations3. User involvement is very important (Joint Application Development (JAD) method)4. Initial prototype must be low cost5. Prototyping essentially bypasses the life-cycle stage of information requirements definition
93 Advantages of Prototyping Short development timeShort user reaction time (feedback from user)Improved users' understanding of the system, its information needs, and its capabilities.Low costDisadvantages and LimitationsGains might be lost through cycles
94 User-Developed DSS advantages End-user development means the developmentand use of computer-based informationsystems by people outside the formal IS areas.1. Short delivery time2. Eliminate extensive and formal user requirements specifications3. Reduce some DSS implementation problems4. Low cost
95 User-Developed DSS Risks 1. Poor Quality2. Quality RisksSubstandard or inappropriate tools and facilitiesDevelopment process risksData management risks3. Increased Security Risks4. Problems from Lack of Documentation5. Problems from Maintenance Procedures
96 Issues in reducing End-User Computing Risks Error detectionUse of auditing techniquesTraining and SupportDetermine the proper amount of controlsInvestigate the reasons for the errorsSolutions
97 Step 2. Requirements Analysis Goal: To understand how DM conceptualizes, analyses, and communicates problems.Direct methodsInterviews, group meetings, JADIndirect methodsObservation, temporary job assignments, questionnaires, document review, software reviewAddressing compiled knowledgeProtocol analysisCard sorting, multidimensional scaling
98 Categorization of DSS Software Specific DSSThe application doing the decision support.DSS generator“Package” that provides capabilities to build SpecificDSSspecial purpose languages, such as IFPSDSS toolstools that facilitate development of a specific DSS or DSS generator3 GLs – 4GLsNow all with Web Hooks and easy GUI interfaces
99 Selection of DSS Development Tools Determine & contact key participantsElicit requirements / functionalityCompose requirements into a RFPDistribute RFPs to potential vendorsCollect and summarize RFP dataSelect RFP short listSet short list interviews and demos; referencesSelect VendorNegotiate contract
100 Complexity of the Software Selection Process 1. DSS information requirement and outputs are not completely known2. Hundreds of software packages3. Software packages evolve very rapidly4. Frequent price changes5. Several people involved
101 6. One language for several DSS? Tool requirements may change 7. Dozens of criteria, some intangible, some conflict8. Technical, functional, end-user, and managerial issues9. Published evaluations are subjective and superficial10.Trade off between open and closed environments
102 Step 5. Implementation as Change From development to productiontechnology acquisitionport to production platformdatabase conversionsystem conversion strategyuser access, training, & ongoing supportdocumentation & maintenanceFrom implementation to institutionalizationexistence does not guarantee useuse does not guarantee success
104 Evaluating DSS Success Technical qualityResponse timeThroughputReliabilityData integrityRequirements coverageDoes what it’s supposed to doUse & usabilityNumber of usersFrequency of useUser-friendlinessAccessibilityEconomic benefitsCost of decisionBenefits of improved decision-makingthe problems of measurement and quantification
105 Benefits of DSS Usage More effective decision making faster assimilation of information and/or identification of problemsexploration of more alternativesvisual comparison of alternative consequences/outcomesenvironment of collaborationMore efficient decision makingreduce the length of the decision cyclereduce the cost of the decision
106 Benefits of DSS Usage (2) Better communication & collaboration among decision makersshared information and shared modelimplicit assumptions made explicitImproved learning process for usersoffset cognitive limitations of decision makers; focus on higher-level thinkingprovide environment for utilizing knowledgeprovide environment for acquiring experience
107 Drawbacks to DSS Usage overemphasize on (rational) decision making versus social, intuitive, and personalized approaches to reaching resolutionassumption of relevanceDSS must address most relevant aspects of decision-making
108 Drawbacks to DSS Usage Unintended transfer of power from decision-maker to DSSbetween decision makersObscuring responsibilityDSS as independent entity that must be “right”tendency to trust DSS and its designers
110 Decisions in the E-Business StrategicManagementTacticalOperationalDecisionsInformationDecision CharacteristicsUnstructuredSemi-structuredStructuredTo 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 ScheduledReportsException ReportsDemand Reportsand ResponsesPush ReportsMajorManagementInformationSystems ReportsThe 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 OLAPServerMulti-dimensionaldatabaseCorporateDatabasesClient PCWeb-enabled OLAPSoftwareData is retrieved from corporate databasesand staged in an OLAP multi-dimensionalOperational DBData MartsData WarehouseOnline 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-AnalysisSensitivity AnalysisGoal-Seeking AnalysisOptimization AnalysisImportantDecisionSupportSystemsAnalytical ModelsDecision 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 GatewayEnterprise Information Portal User InterfaceSearchAgentsOLAPDataMiningKnowledgeManagementDatabase Management FunctionsMartOtherBusinessApplicationsOperationalDatabaseAnalyticalBaseDSSWhat-If ModelsSensitivity ModelsGoal-Seeking ModelsOptimization ModelsInternetIntranetExtranetCross-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 CognitiveScienceApplicationsArtificialIntelligenceRoboticsNaturalInterfaceExpert SystemsFuzzy LogicGenetic AlgorithmsNeural NetworksVisual PerceptionsLocomotionNavigationTactilityNatural LanguageSpeech RecognitionMultisensory InterfaceVirtual RealityArtificial 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 NetworksFuzzy Logic SystemsVirtual RealityExpert SystemsAI ApplicationAreas inBusinessIntelligent AgentsGenetic AlgorithmsThere 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 SystemKnowledgeBaseUserWorkstationExpertAdviceInterfaceProgramsInferenceEngineProgramExpert System DevelopmentEngineeringAcquisitionExpert and/orKnowledge EngineerAn 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 ManagementDiagnostic/TroubleshootingMaintenance/SchedulingDesign/ConfigurationSelection/ClassificationMajorApplicationCategoriesof Expert SystemsProcess Monitoring/ControlExpert 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 SummaryDSS 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 NetworksFuzzy LogicGenetic AlgorithmsVirtual RealityIntelligent Agents
122 References Efraim Turban & Jay E. Aronson “ Decision Support Systems and IntelligentSystems “Prentice Hall, Upper Saddle River, NJ (1998)