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Data Analyst

A comprehensive guide for Data Analyst

""1PREREQUISITES & FUNDAMENTALS2SPREADSHEET MASTERY3RELATIONAL DATABASES AND SQL4BUSINESS INTELLIGENCE (BI) AND DATA VISUALIZATION5PROGRAMMING FOR DATA ANALYSIS (PYTHON OR R)6DATA CLEANING AND PREPARATION7ADVANCED STATISTICS AND EXPLORATORY DATA ANALYSIS (EDA)8BUSINESS ACUMEN AND SOFT SKILLS9BUILDING A PORTFOLIO AND CAREER PREPARATIONData AnalystBasic Mathematics and StatisticsDescriptive StatisticsMeanMedianModeVarianceStandard DeviationSkewnessKurtosisProbability BasicsDistributionsBayes TheoremExpected ValueInferential StatisticsHypothesis Testingp-valuesA/B TestingConfidence IntervalsMargin of ErrorComputer Literacy & ToolingFile Systems and DataFormatsCSVJSONXMLParquetAvroCommand Line BasicsNavigating directoriesbasic shell commandsVersion Control BasicsGitGitHubCommitsBranchesPull RequestsMerge ConflictsEnvironment ManagementVirtual environmentspipcondaGenerative AI for DataPrompt EngineeringLLM Coding Assistantslike Copilot/ChatGPTData Ethics, Privacy, and GovernanceData Privacy LawsGDPRCCPAHIPAA basicsData Anonymization andPII HandlingBias in Data andEthical AnalysisData GovernanceData CatalogsAccess ControlData LineageBasic Operations and FormattingData Entry,Validation, and DataTypesCell Formatting,ConditionalFormatting, and CustomFormatsKeyboard Shortcuts andProductivity HacksFormulas and FunctionsMathematical andStatistical FunctionsSUMAVERAGECOUNTCOUNTIFSSUMIFSLogical FunctionsIFANDORIFERRORIFSLookup and ReferenceFunctionsVLOOKUPHLOOKUPINDEXMATCHXLOOKUPText and Data CleaningFunctionsLEFTRIGHTMIDCONCATENATETEXTJOINTRIMFINDREPLACEDate and TimeFunctionsTODAYNOWDATEDIFEOMONTHWORKDAYModern Dynamic ArraysFILTERSORTUNIQUESEQUENCEData Analysis Tools in SpreadsheetsPivot Tables and PivotChartsData Sorting,Filtering, andAdvanced FiltersWhat-If AnalysisGoal SeekData TablesScenario ManagerPower Query BasicsImportingtransformingmergingand cleaning dataAutomation BasicsMacrosVBAor Google Apps ScriptoverviewDatabase Fundamentals and ModelingRelational DatabaseConceptsTablesRowsColumnsSchemasKeys and RelationshipsPrimary KeysForeign KeysOne-to-ManyMany-to-ManyNormalization (1NF,2NF, 3NF) and DataIntegrity RulesEntity-RelationshipDiagrams (ERDs) andSchema DesignDimensional ModelingDeep DiveFact vs. DimensionTablesSlowly ChangingDimensions - SCD Types1/2/3Basic SQL QueriesData RetrievalSELECTFROMWHERE clausesSorting and LimitingResultsORDER BYLIMITTOPOFFSETFiltering DataLIKEINBETWEENIS NULLBoolean OperatorsIntermediate SQLAggregate FunctionsCOUNTSUMAVGMINMAXGrouping DataGROUP BYHAVINGAliasing (AS) and TypeCastingCASTCONVERTString, Date, and MathManipulation FunctionsAdvanced SQLJoinsINNERLEFTRIGHTFULL OUTERCROSSSELFSet OperationsUNIONUNION ALLINTERSECTEXCEPTSubqueries and CommonTable ExpressionsCTEs - WITH clauseWindow FunctionsROW_NUMBERRANKDENSE_RANKLEADLAGNTILEOVERPARTITION BYAdvanced Data TypesWorking with JSON andArrays in SQLDynamic SQL and StoredProceduresBasicsPerformance, Data Warehousing, and Modern Data StackQuery Optimization,Execution Plans, andSARGable QueriesIndexing StrategiesClustered vs.Non-ClusteredData WarehousingConceptsOLTP vs. OLAPStar and SnowflakeSchemasCloud Data WarehousesSnowflakeBigQueryRedshift overviewModern Data Stack andELTdbtFivetranAirbyte basicsData Visualization PrinciplesChoosing the RightChart Type for theData StoryColor Theory,Typography, andAccessibility inDashboardsCognitive Load andGestalt Principles inDesignData Storytelling andAudience ContextAnalysisBI Tool Fundamentals (Tableau, Power BI, or Looker)Connecting to VariousData SourcesFilesDatabasesCloudCreating BasicVisualizationsBar chartsLine chartsScatter plotsMapsHeatmapsUnderstandingDimensions vs.Measures, Discrete vs.Continuous DataFormatting andTooltips forInteractivityAdvanced BI TechniquesCalculated Fields,Parameters, and Levelof Detail (LOD)ExpressionsTableauData AnalysisExpressions (DAX) andData ModelingPower BIBuilding InteractiveDashboards, Actions,and Drill-downsData Blending,Relationships, andCross-Database JoinsDashboard PerformanceOptimization andRendering BestPracticesPublishing, SchedulingExtracts, andRow-Level SecurityRLSProgramming FundamentalsVariables, Data Types,and OperatorsControl FlowIf/Else statementsFor/While loopsFunctions, Scope,Lambda Functions, andError HandlingData StructuresListsDictionariesTuplesSets / VectorsData FramesData Manipulation (Pandas for Python / Tidyverse for R)Understanding Seriesand DataFrames(Python) / TibblesRImporting andExporting Dataread_csvread_sqlto_excelread_parquetIndexing, Selecting,Filtering, and SortingDataHandling Missing Data(Imputation, Drop) andDuplicatesGrouping, Aggregating,and Transforming DataMerging, Joining, andConcatenating DatasetsReshaping DataMeltPivot / GatherSpreadNumerical ComputingNumPy Arrays,Broadcasting, andVectorizationPythonMathematical andStatistical Operationson Multi-dimensionalArraysData Visualization in ProgrammingMatplotlib and SeabornBasics (Python) /ggplot2RCustomizing PlotsAxesLegendsThemesAnnotationsCreating InteractivePlotsPlotlyBokehor AltairInteractive Environments and Software Engineering Best PracticesJupyter Notebooks andJupyterLabMarkdown forDocumentation withinNotebooksCode ModularityTransitioning fromNotebooks to .py/.RscriptsBasic Version Controlin Data ProjectsGitHub flows for dataanalysisData Quality AssessmentProfiling Data andIdentifyingOutliers/AnomaliesHandling InconsistentData Formats and TyposValidating Dataagainst Business RulesData Transformation TechniquesData Normalization,Standardization, andScalingEncoding CategoricalVariablesOne-Hot EncodingLabel EncodingFeature EngineeringCreating new metricsbinningdate extractionText Cleaning andRegular ExpressionsRegexData Acquisition and APIsInteracting with RESTAPIsPaginationAuthenticationJSON parsingBasics of HTML, CSSSelectors, and HTTPrequestsWeb Scraping librariesBeautifulSoupScrapySeleniumData Validation and Automated TestingAutomated Data TestingConceptse.g.dbt testsGreat ExpectationsSchema Validation andType Checkinge.g.Pydantic basicsComprehensive EDA ProcessUnivariate AnalysisExaminingdistributionshistogramsbox plotsBivariate andMultivariate AnalysisScatter plotscorrelation matricescross-tabulationIdentifyingCorrelation vs.CausationSpurious correlationsconfoundersApplied Statistical MethodsLinear RegressionSimple and MultipleRegressionR-squaredResidualsLogistic RegressionBasics ofclassificationodds ratiosROC/AUCA/B Testing Deep DiveSample sizestatisticalsignificanceType I & II errorsPower analysisTime Series AnalysisBasicsTrendsSeasonalityMoving AveragesForecastingClustering BasicsK-MeansCustomer SegmentationCohort Analysis andCustomer LifetimeValueCLVSurvival AnalysisBasicsRetention curvesCausal InferenceBasicsDifference-in-DifferencesPropensity ScoreMatching - OverviewDomain Knowledge and Product AnalyticsUnderstanding KeyPerformance Indicators(KPIs) and Metrics byIndustryE-commerceSaaSFinanceHealthcareMarketingProduct AnalyticsAARRR MetricsFunnel AnalysisUser EngagementTranslating AmbiguousBusiness Problems intoStructured DataQuestionsROI, Impact Analysis,and Cost-BenefitAnalysisCommunication and PresentationPresenting DataFindings toNon-TechnicalStakeholdersEffectivelyWriting Clear,Concise, andActionable DataReports/MemosExecutive SummariesThe Art of Persuasionand Driving Decisionswith DataProblem Solving, Workflow, and Critical ThinkingStructured ThinkingFrameworkse.g.MECEIssue TreesRoot Cause Analysis5 WhysFishbone DiagramsAgile/Scrum for DataTeamsSprintsKanbanJira/Trello basicsStakeholder Managementand ExpectationSettingPersonal ProjectsFinding and EvaluatingOpen DatasetsKaggleData.govGoogle Dataset SearchAWS Open DataEnd-to-End AnalysisProjectsFrom raw dataextraction toactionable businessinsightsDocumenting Projectson GitHubClear READMEswell-commented JupyterNotebooksCreating a PublicDashboardTableau PublicPower BI ServiceProfessional PresenceOptimizing LinkedInProfile and Resume forApplicant TrackingSystems (ATS) and DataRolesBuilding a PersonalWebsite or PortfolioSitee.g.GitHub PagesNotionMediumNetworking and TechBloggingSharing insights onLinkedIn or MediumInterview PreparationTechnical ScreeningsLive SQL queryingPython/PandasmanipulationExcel testsLeetCode for DatabaseCase Study InterviewsTake-home assignmentspresentation roundsguesstimatesBehavioral InterviewsSTAR method forcommunicating pastexperiences andcross-functionalcollaboration