Data warehousing for biomedical informatics

Content: Biomedical Data WarehousingNature of Biomedical DataNature of Warehoused DataBusiness RequirementsFunctional RequirementsNever-Finished WarehouseOrganizational ReadinessImplementation StrategySECTION I ALPHA VERSIONDimensional Data ModelingEvolution of Data WarehousesThe Star SchemaTransposing Dimensional SchemaAnticipating DimensionsAffinity AnalysisUnderstanding Source DataImplicit versus Explicit DataSemantic LayersInformation ArtifactsBiomedical ContextClinical PictureOntological LevelsEpistemological LevelsConclusionsBiomedical WarehouseBiomedical StarBiomedical FactsMaster DimensionsReference DimensionsAlmanac DimensionsAnalysis DimensionsControl DimensionsRequirements AlignmentStar Dimension Design PatternStructure of a DimensionMaster Data: Definition TablesSlowly Changing DimensionsSource Keys: Context and Reference TablesFact Participation: Group and Bridge TablesInterconnections: Hierarchy TablesConnecting to FactsDimension NavigationLoading Alpha VersionThrow-Away CodeSelecting and Preparing SourcesGenerating Surrogate KeysSimple Dimensions and FactsRecap of Simple ETLsComplicated Dimensions and FactsFinalizing Alpha StructuresV&V of Alpha VersionSECTION II BETA VERSIONCompleting the DesignUnit of MeasureMetadata MappingsControl DimensionsReinitializing the WarehouseData SourcingSource Mapping ChallengesDimensionalizing FactsSourcing Your DataGeneralizing ETL WorkflowsStandardizing Source DataSource Data Intake JobsSDI Design PatternSource Data ConsolidationExternal versus Internal SourcingSingle Point of FunctionETL "Pipes"Metadata TransformationData Control PipeWide versus Deep DataETL Reference PipeMetadata TransformationReference CompositeResolve ReferencesUnresolved ReferencesReference EntriesAlias EntriesBridges and GroupsHierarchy EntriesFiat HierarchiesNatural HierarchiesETL Definition PipeProcessing ComplexitiesExample Master LoadsInsert New DefinitionsNew OrphansOrphan Auto-AdoptionDefinition Change ProcessingBuilding SCD Transaction SetsApplying Transactions to DimensionsPerformance ConcernsETL Fact PipeMetadata TransformationBridges and GroupsBuild FactsFinalize DimensionsSet Control DimensionsInsert Fact ValuesSuperseding FactsFinalizing BetaAudit Trail FactsDatafeed DimensionVerification and ValidationPreparing for GammaSECTION III GAMMA VERSIONFinalizing ETL WorkflowsAlternatively Sourced KeysSourced MetadataStandard Data EditingValue-Level UOMUndetermined DimensionalityETL TransactionsTarget StatesSuperseded FactsContinuous Functional EvolutionEstablishing Data ControlsFinalizing Warehouse DesignRedaction Control SettingsData MonitoringSurrogate MergesSecurity ControlsImplementing Dataset ControlsWarehouse Support TeamBuilding out the DataMinimize Data SeamsShifting toward MetricsPopulating Metric ValuesPopulating Control ValuesPopulating DisplaysDelivering DataWarehousing Use CasesPrivacy-Oriented Usage ProfilesMetadata BrowsingCohort IdentificationFact Count QueriesTimeline GenerationBusiness IntelligenceAlternative Data ViewsFinalizing GammaBusiness RequirementsTechnical ChallengesFunctional ChallengesGoing LiveSECTION IV RELEASE 1.0Knowledge SynthesisFact CountsDerivative DataTimeline AnalysisStatistical AnalysesStatistical Process ControlSemantic AnnotationData GovernanceOrganizing for GovernanceGovernance OpportunitiesIndex