The analytics process strategic and tactical steps
ANALYTICS PROCESS CONCEPTS About the Analytics ProcessThe Roots and Pillars of Analytics WorkUsing Analytics in ManagementManaging Analytics KnowledgeAnalytics Knowledge: Intelligence, Decisions, and MeaningIntelligenceDecision-Making ProcessMeaningWhat Are the Types of Questions, Problems, and Tasks in Analytics?Thinking about Data and AnalyticsThe Concepts of Small Data, Big Data, and Great DataMeasurement ProcessWho Are Analytics Professionals?First Steps in Analytics Process DesignReferencesIllustrating the Analytics Process through Risk Assessment and ModelingObserving Great Data in the Context of RMBases for Building an ERKMASDeveloping Risk-Modeling Knowledge: The Analytics ApproachKnowledge CreationKnowledge Storage and RetrievalKnowledge TransferKnowledge Application and LearningConclusionsReferencesAnalytics, Strategy, and Management Control SystemsBreaking Paradigms and Organizations as SystemsOrganizations and Management Control SystemsKey Performance Indicators and Key Risk IndicatorsReferencesANALYTICS PROCESS APPLICATIONSData, Information, and IntelligenceIntroductionPurpose of the StudyAbout the Background of This WorkWhat Is the Scope of This Work?Definition of the Key ConceptsWhat Is the Work Performed in This Field?Knowledge-Based View of the FirmData, Information, Knowledge, and Wisdom or Intelligence (DIKW)KM and Intellectual CapitalLeveraging KnowledgeKnowledge and IntelligenceBig Data and Business AnalyticsDescription of the ProblemResearch Questions or HypothesesWhat Was the Methodology of the Problem Resolution?What Was the Data Used For?What Were the Models and Concepts Used in This Study?About Validity and Reliability in This WorkWhat Were the Results and Their Meaning or Context?How Are These Results Meaningful for Organizations and for Future Research?Where, How, and When to Use It?Conclusions and RecommendationsAre the Objectives of the Research Achieved?StrategicAcknowledgmentReferencesThe Rise of Big Data and Analytics in Higher EducationIntroductionDevelopment of Big DataOverview of Big Data ResearchAnalytics and Big Data in Higher EducationConceptualizing Big Data in Higher EducationInstitutional AnalyticsInformation Technology AnalyticsAcademic or Program AnalyticsLearning AnalyticsSources and Types of Big Data in Higher EducationOpportunitiesChallenges of ImplementationSummary and Future DirectionsAuthor's NotesReferencesGoogle Analytics as a Prosumption Tool for Web AnalyticsIntroductionPurpose of the StudyAbout the Background of This WorkWhat Is the Scope of This Work?Definition of the Key ConceptsWhat Is the Work Performed in This Field?General Assumptions about Web AnalyticsMeasurementAnalysisReportingConclusion DevelopmentThe Accomplishment of Case Study GoalsDescription of the Problem and Method to Solve ItDefinition of the Problem That Is AnalyzedResearch Questions or HypothesesWhat Was the Methodology of the Problem Resolution?How Was the Research Designed?What Data Was Used?What Were the Results and Their Meaning/Context?Why Is This Approach to the Solution Valuable?What Are the Results and Their Interpretation?How Are These Results Meaningful for Organizations and for Future Research?Where, How, and When to Use It?Conclusions and RecommendationsAre the Objectives of the Research Achieved?Operational and TacticalStrategicReferencesKnowledge-Based Cause-Effect Analysis Enriched by Generating Multilayered DSS ModelsIntroductionPurpose of the StudyAbout the Background of This WorkWhat Is the Scope of This Work?Definition of the Key ConceptsWhat Data Was Used?What Were the Models and Concepts Used in This Study?Knowledge RepresentationKnowledge ReasoningDSS Model OutputReferencesOnline Community Projects in Lithuania: Cyber Security PerspectiveIntroductionPurpose of the StudyAbout the Background of This WorkWhat Is the Scope of This Work?Definition of the Key ConceptsWhat Is the Work Performed in This Field?Theories and Models Used for Approaching the ProblemDescription of the ProblemDefinition of the Problem That Is AnalyzedResearch Questions or HypothesesWhat Was the Methodology of the Problem Resolution?How Was the Research Designed?What Were the Data, Models, and Tests Used?What Were the Models and Concepts Used in This Study?What Was the Way to Test/Answer the Hypotheses/Research Questions?What Were the Results and Their Meaning or Context?Why Is This Approach to the Solution Valuable?What Are the Results and Their Interpretation?How Are These Results Meaningful for Organizations and for Future Research?Where, How, and When to Use It?Conclusions and RecommendationsAre the Objectives of the Research Achieved?ReferencesExploring Analytics in Health Information Delivery to Acute Health Care in AustraliaIntroductionPurpose of the StudyAbout the Background of This WorkWhat Is the Scope of This Work?Contextual TaxonomiesWhat Is the Work Performed in This Field?Theories and Models Used for Approaching the ProblemDescription of the ProblemDefinition of the Problem That Is AnalyzedResearch Questions or HypothesesWhat Was the Methodology of the Problem Resolution?How Was the Research Designed?What Data Was Used?What Were the Models and Concepts Used in This Study?Visualizing Data Governance in Health Care PracticesHow Were the Hypotheses/Research Questions Tested/Answered?Scenario Analysis: The Need for Data GovernanceScenario 1: Scrutinizing the Business Case of an Operating Theater in the State of VictoriaScenario 2: Information Focus in a Public Primary Care ProviderScenario 3: Influence of Genomic DataScenario 4: Optimizing IncomeScenario 5: Campus, Network, and RegionalScenario 6: Cancer Research Information Exchange FrameworkAbout the Validity and Reliability in This WorkWhat Were the Results and Their Meaning/Context?Why Is This Approach for the Solution Valuable?What Are the Results and Their Interpretation?How Are These Results Meaningful for Organizations and for Future Research?Where, How, and When to Use It?Conclusions and RecommendationsWere the Objectives of the Research Achieved?Operational and TacticalStrategicReferencesInformation Visualization and Knowledge Reconstruction of RFID Technology Translation in Australian HospitalsIntroductionPurpose of the StudyAbout the Background of This WorkThe Australian Health MilieuWhat Is the Scope of This Work?Definition of the Key ConceptsWhat Is the Work Performed in This Field?Description of the ProblemDefinition of the Problem That Is AnalyzedResearch Questions or HypothesesWhat Was the Methodology of the Problem Resolution?How Was the Research Designed?Developing the Conceptual FrameworkWhat Data Was Used?What Were the Models and Concepts Used in This Study?Intersection of Innovation Translation and ANTIn What Way Were the Hypotheses/Research Questions Tested/Answered?About Validity and Reliability in This WorkWhat Were the Results and Their Meaning/Context?Why Is This Approach for the Solution Valuable?What Are the Results and Their Interpretation?How Are These Results Meaningful for Organizations and for Future Research?Where, How, and When to Use It?Conclusions and RecommendationsAre the Objectives of the Research Achieved?Operational and TacticalStrategicReferencesHealth Care Analytics and Big Data Management in Influenza Vaccination Programs: Use of Information- Entropy ApproachIntroductionPurpose of the StudyAbout the Background of This WorkWhat Is the Scope of This Work?Definition of the Key ConceptsDescription of the ProblemResearch Questions or HypothesesWhat Was the Methodology of the Problem Resolution?How Was the Research Designed?What Data Was Used?What Were the Models and Concepts Used in This Study?What Was the Way to Test/Answer the Hypotheses/Research Questions?What Are the Results and Their Interpretation?How Are These Results Meaningful for Organizations and for Future Research?Conclusions and RecommendationsAre the Objectives of the Research Achieved?AcknowledgmentReferencesSharing Knowledge or Just Sharing Data?IntroductionThe Big Dangers of Big DataDefining the Key ConceptsGetting Started with AnalyticsKnowledge and the Need to Share ItKnowledge Sharing: Easier Said Than DoneExamples of Success and Failure in Knowledge SharingConclusionsReferences
