Data Quality Scorecard - ELearningCurve

Data QualityScorecardby Olga Maydanchik 2019 by eLearningCurve LLC. All rights reserved. Reproduction in whole or part prohibited except by written permission.Product and company names mentioned herein may be trademarks of their respective companies.

DQ-09: Data Quality ScorecardModule 0. About the Course (3 min)Module 1. Case Studies (46 min) What is Data Quality Assessment?What is a Data Quality Scorecard?Data Quality Scorecard Case Study #1: Improving the Efficiency of the RiskWeighted Asset (RWA) Calculation Process (Financial Company)o Data Quality Scorecard Goalo RWA Calculation Processo Solution Stepso Case Study 1 DQ Scorecard Componentso Field Scoreso Field Score Vs. EADo List of Rules Affecting DQ Scoreo Rule Error Listo Business Process DQ Scoreo DQ Score Decomposition By Instrument Typeo DQ Score Decomposition By Asset Delinquencyo Case Study 1 SummaryData Quality Scorecard Case Study #2: Data Quality Impact on CatastropheRisk Modeling (Insurance Company)o Catastrophe Insuranceo Catastrophe Risk Modelingo DQ Scorecard Goalo Case Study 2 Data Quality Scorecard Componentso Data Quality Factor Vs. Structure Insured Valueo The Cost of Poor Data Qualityo Data Quality Factor Analyticso Rules for Data Elemento Business Case for Data Quality Improvemento Case Study 2 SummaryModule 2. Data Quality Score Calculation Methods (37 min) Page 2Averages Method For Score Cardso Averages Method Score Calculation Exampleo Averages Score Calculations Drawbacks: Part 1o Averages Score Calculations Drawbacks: Part 2Record-Level Score Calculationso Record-Level Score Calculation Formulao Record-Level (RL) Close Parenthesis Score Calculation ExampleSubject-Level Score Calculationso What Are Subjectso Subject-Level (SL) Score Calculation Formulao Subject-Level (SL) Score Calculation Example 1o Subject-Level (SL) Score Calculation Example 2Score Types ComparisonsScore Decomposition By Business Dimensionso Score Decomposition Exampleso DQ Assessment Granular Results 2019 by eLearningCurve LLC.

DQ-09: Data Quality Scorecard o Scores Calculated From Granular Resultso DQ Scores VisualizationBusiness Dimensions Versus Subjectso Overviewo HR Exampleo Manufacturing Exampleo Insurance ExampleModule SummaryModule 3. Data Modeling Considerations Part 1 (55 min) Why DQMDW?DQMDW ComponentsCase Study DQMDW For Property Insurance CompanyDQMDW: Critical Data Elements Catalogo Technology Landscapeo Technology Landscape - Data Exampleo Critical Data Elements - Definitiono Critical Data Elements Exampleo Critical Did Elements In DQMDWo Enterprise Data Modelo EDM & DQMDWo Critical Data Elements - Data Exampleo Business Process Taxonomy And DQMDWo Business Process Taxonomy – Data Exampleo CDE Catalog - Putting It All TogetherDQMDW: Rule Catalogo Rule Catalog - Overviewo Rules – Thresholdo Rules – Governanceo Rules – DQ Dimensionso Rules – Life Cycleo Rules – Execution Typeo Rule Error Captiono DQ Rule Error Output - Exampleo Rule Error Output - Purposeo DQ Rule Error Output - Dashboard Exampleo Analysis Exampleo DQ Rule Error Output - Where To Recordo Rule Instance - Data Exampleo Rule Catalog - Data ExampleModule 4. Data Modeling Considerations Part 2 (68 mins) Page 3DQMDW: Subject Master And Business Dimensions Mastero Subject Master Lists - Overviewo Dimensions Master List - Overviewo Master Lists Vs Reference Datao Subject Master – Data Exampleo Business Dimensions Master – Data Exampleo Subject Master - Additional Fields 2019 by eLearningCurve LLC.

DQ-09: Data Quality Scorecard DQMDW: Error Catalogo Error Catalog Overviewo DQ Assessment Results – Assessment Infoo DQ Assessment Results – Record Infoo DQ Assessment Results – Subjects And Dimensions Infoo DQ Assessment Results – Data Exampleo Granular Results – Rule Versioning Decisionso Periodic Assessments – How Much History To Keepo Hierarchical Subjects – Error Treatment DecisionsError Details – Storage Optionso Error Details Tableo Option 1: XMLo Option 2: Delimited Fieldso Option 3: Multiple RowsRule Error Output – Advanced Exampleso One Error Affects Two Recordso One Error Affects Many Recordso Two Errors For The Same SubjectDQMDW: Score Catalogo DQ Scores - Overviewo Score History – Score Ido Score History – Score Typeo Score History – Score Valueo Score History – Objecto Score History – Business Dimensiono Score History – Data Example SLo Score History – Data Example RLDataMarts For DQ Visualizationo DQ Visualization Stepso Step 1: Create Visualization Requirementso Step 2: To Create Screen Mock Upso Step 3: Create DataMart Supporting Visualizationo DataMart For Score Hierarchyo DataMart - Data Exampleo Score Catalog SummaryModule 5. Building a Data Quality Scorecard Process (61 mins) Page 4Process OverviewStep 1: Define The DQ Assessment And DQ Scorecard Scopeo How To Define The Scopeo Why Limit The Data Volumeo How To Limit The Data Volumeo Why Not Use Random Data SampleStep 2: Populate The Staging Areao Load Data Into Staging AreaStep 3: Prepare The Datao Data Preparation Taskso Why Do We Need To Prepare DataStep 3A: Add Record ID StepStep 3B: Fill Dataset AsOfDate 2019 by eLearningCurve LLC.

DQ-09: Data Quality Scorecard Step 3C: Create/Update Subject Master Listo Subject Master Exampleo Why Create Subject Mastero How To Create Subject Mastero Using Subject Master To Speed Up Developmento Subject HierarchiesStep 3D: Create/Update Business Dimension Master Listso How To Come Up With Business Dimensionso When To Create Business Dimension MasterStep 4: Perform Data Profilingo Data ProfilingStep 5: Create and Code Data Quality Ruleso DQ Rules Sourceso Coding DQ Ruleso DQ Rules Logic Templateo DQ Rules Logit Template Cons 1 & 2Step 6: Run DQ Ruleso Rule Execution Treeo Rule Execution Tree Exampleso Rule Execution Process Designo Rule Execution and Score Calculation OptionsStep 7: Move Rule Execution Results into DQMDWo Rule Results TransformationStep 8: Calculate Aggregate Scoreso OLAP Cube for Unlimited Number of DQ Scoreso Calc Engine for Pre-Selected Scoreso Visualization Tool for Score CalculationStep 9: Examine DQ Scores and DQ Rule Resultso Examining Rule Resulto Control Chartso Control Charts in Data QualityStep 10: Fine-Tune Data Quality Ruleso Rule Fine-Tuningo Using Profiling Techniqueso Cyclical Nature of the Rule-Fine TuningModule 6. Data Quality Scorecard Demo (35 mins) Page 5Overall Score Analysiso Screen Look And Feelo DQ Score Column – Size Color Sorting Tooltipo DQ Score Column – Filteringo How Field Errors Affect Business Processeso Data Quality Score Prioritization Quadranto DQ Work Prioritization Steps - 1o DQ Work Prioritization Steps - 2o Score Prioritization Ideaso Customer Volumeo Customer Lifetime Valueo DQ Score Timeline Columno Rule Details Drill Down Functionalityo Rule Details Error Profileso Demo SummarySummary 2019 by eLearningCurve LLC.

DQ-09: Data Quality Scorecardo Key Definitiono Key DQ Score Calculation Conceptso Typical DQ Scorecard Components and FeaturesPage 6 2019 by eLearningCurve LLC.

o DQ Scorecard Goal o Case Study 2 Data Quality Scorecard Components o Data Quality Factor Vs. Structure Insured Value o The Cost of Poor Data Quality o Data Quality Factor Analytics o Rules for Data Element o Business Case for Data Quality Improvement o Case Study 2 Summary Module 2. Data Quality Score Calculation Methods (37 min)