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Applied Big Data Analytics in Operations Management

PrefaceBig Data in Operation ManagementLITERATURE SURVEYRESEARCH ROADMAPINTRODUCTION TO BIG DATABIG DATA OPERATION MANAGEMENTReal Time Data CollectionReal Time Event ProcessingComprehensive Data CollectionDeterministic Data CollectionVARIOUS APPROACHES AND USE CASES TO BIG DATA OPERATION MANAGEMENTSplunk Approach to Big Data Operations ManagementReflex System Approach to Big Data Operation ManagementThe Cloud Physics Approach to Big Data Operation ManagementXangati Approach to Big Data Operation ManagementCOMPARATIVE ANALYSES OF VARIOUS APPROACHESCONCLUSIONREFERENCESADDITIONAL READINGKEY TERMS AND DEFINITIONSApplication of Artificial Neural Networks in Predicting the Degradation of Tram Tracks Using Maintenance DataINTRODUCTIONBackgroundStatement of ProblemResearch ObjectivesTRAJECTORY DATAInspection DataLoad DataImpact of RepairDATA ANALYSISTrack Deterioration Profile Over TimeImpact of Repair on Deterioration ProfileImpact of Other Factors on DeteriorationContinuous VariablesCategorical VariablesRESEARCH METHODOLOGYArtificial Neural NetworksA Model to Predict Gauge WideningRESULTSCONCLUSION AND RECOMMENDATIONSFUTURE RESEARCH DIRECTIONSREFERENCESADDITIONAL READINGKEY TERMS AND DEFINITIONSZAMREN Big Data Management (ZAMBiDM) Envisaging Efficiency and Analytically Manage IT ResourcesStatement of the ProblemObjective of the ZAMBiDMOrganisation of the ChapterLITERATURE REVIEWBig DataData ManagementBig Data ManagementBig Data StrategiesBig Data AnalyticsBig Data VirtualisationZambia Research Education Network (ZAMREN)THE PROPOSED ZAMBiDM MODELThe ZAMREN Big Data and Data Management ComponentZAMBiDM VirtualisationZAMBiDM Strategies and Operational Processes/NodesAnalytic ToolsData Quality ToolsElevate Data to Executive LevelRoad Map Manage Big DataIMPLEMENTATION OF ZAMBiDMCONCLUSIONREFERENCESPredictive Analytics in Operations ManagementPREDICTIVE ANALYTICSTYPEPredictive ModelsDescriptive ModelsDecision ModelsPREDICTION IN OPERATIONS MANAGEMENTRELATED WORKANALYTICAL TECHNIQUESRegression TechniquesMachine Learning TechniquesMAPREDUCEREGRESSION TECHNIQUESLinear Regression ModelMACHINE LEARNING TECHNIQUESParallel BackpropagationImplementationParallel Support Vector MachineRECENT RESEARCHESCONCLUSIONREFERENCESKEY TERMS AND DEFINITIONSPros and Cons of Applying Opinion Mining on Operation Management: A Big Data PerspectivePROS AND CONS FRAMEWORKFake Reviews, Leading to Opinion FraudsThreats from Illegitimate DataSENTIMENT ANALYSIS IN OPERATION MANAGEMENT USING BIG DATACONCLUSION AND FUTURE RESEARCHREFERENCESADDITIONAL READINGKEY TERMS AND DEFINITIONSA Conceptual Framework for Educational System Operation Management Synchronous with Big Data ApproachOPERATIONAL MANAGEMENT IN EDUCATIONAL SYSTEMADOPTION OF ICT OPERATIONS IN EDUCATIONAL SYSTEMOperations Based on Educational Management Information SystemOperations Based on Learning Management SystemCOMPLEXITIES IN EXISTING EDUCATIONAL OPERATIONAL MANAGEMENTComplexities in Data ManagementEXISTING OPERATIONAL TECHNIQUES TO STORE/PROCESS BIGDATAAbout BigData StorageBenefits of BigData StorageObstructions towards BigData UsageExisting Operational Tools in Educational BigDataSIGNIFICANT ISSUES IN EXISTING OPERATIONAL TECHNIQUESCONCEPTUALIZED FRAMEWORK OF NOVEL EDUCATIONAL OPERATIONAL MANAGEMENTProposed MethodologyPossible Advantages of Conceptual FrameworkResearch ImplicationBenefits and Disadvantage of Conceptual Framework in Operation ManagementCONCLUSIONREFERENCESKEY TERMS AND DEFINITIONSManagement of SME’s Semi Structured Data Using Semantic TechniqueBACKGROUNDCharacteristics of Big DataSEMANTIC WEB LANGUAGESSYNTHETIC SEMANTIC DATA MANAGEMENTPropertiesInference RuleSPARQLSSDM Implementation StepDevelopment of Core OntologyFinding of Synthesis Data and Convert to RDBDevelopment of Domain Ontologya. Mapping Relational Schema to Ontologyb. Mapping Attributesc. Mapping Constraintsd. Data ExtractionSOLUTIONCONCLUSIONREFERENCESAn Overview of Big Data Security with Hadoop FrameworkINTRODUCTIONBIG DATA TECHNOLOGIESWORKING OF HADOOP FRAMEWORKPAST RESEARCHES ON BIG DATA SECURITYSECURITY ISSUES AND CHALLENGES RELATED TO BIG DATASECURITY SOLUTIONS NEEDED FOR BIG DATAa. Authenticationb. Authorizationc. Accountabilityd. Data Protectione. Integrity VerificationSUMMARYRESEARCH SCOPEREFERENCESADDITIONAL READINGKEY TERMS AND DEFINITIONS

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