DQ-09 Data Quality Scorecard

Module 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 Risk-Weighted Asset (RWA) Calculation Process (Financial Company)
• Data Quality Scorecard Case Study 2: Data Quality Impact on Catastrophe Risk Modeling (Insurance Company)

Module 2. Data Quality Score Calculation Methods (37 min)

• Averages Method For Score Cards
• Record Level Score Calculations
• Subject Level Score Calculations
• Score Types Comparisons
• Score Decomposition By Business Dimensions
• Business Dimensions Versus Subjects

Module 3. Data Modeling Considerations Part 1 (55 min)

• Why DQMDW?
• DQMDW Components
• Case Study DQMDW For Property Insurance Company
• DQMDW: Critical Data Elements Catalog
• DQMDW: Rule Catalog

Module 4. Data Modeling Considerations Part 2 (68 min)

• DQMDW: Subject Master And Business Dimensions Master
• DQMDW: Error Catalog
• Error Details – Storage Options
• Rule Error Output – Advanced Examples
• DQMDW: Score Catalog
• DataMarts For DQ Visualization

Module 5. Building A Data Quality Scorecard Process (61 min)

• Process Overview
• Step 1 Define The DQ Assessment And DQ Scorecard Scope
• Step 2: Populate The Staging Area
• Step 3: Prepare The Data
• Step 3A: Add Record ID Step
• Step 3B: Fill Dataset AsOfDate
• Step 3C: Create/Update Subject Master List
• Step 3D: Create/Update Business Dimension Master Lists
• Step 4: Perform Data Profiling
• Step 5: Create and Code Data Quality Rules
• Step 6: Run DQ Rules
• Step 7: Move Rule Execution Results into DQMDW
• Step 8: Calculate Aggregate Scores
• Step 9: Examine DQ Scores and DQ Rule Results
• Step 10: Fine-Tune Data Quality Rules

Module 6. Data Quality Scorecard Demo (35 min)

• Overall Score Analysis
• Summary

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