Data Quality Engineering in Financial Services

Table of contents

1. Preface
   1. My Journey and a Brief History of Data in the Financial Services Industry
   2. Conventions Used in This Book
   3. Online Figures
   4. O’Reilly Online Learning
   5. How to Contact Us
   6. Acknowledgments
2. 1. Thinking Like a Manufacturer
   1. Operational Efficiency
   2. Lessons from Lean Manufacturing
      1. Coca-Cola: Excellence in Manufacturing Quality
      2. DASANI®: Purifying Water
   3. Manufacturing Control Specifications
      1. Water Quality Specifications
      2. Quality Control and Anomaly Detection
   4. Summary
3. 2. The Shape of Data
   1. Data as Physical Asset
   2. Data Shape Concept Model
      1. Data Element
      2. Datum
      3. Data Universe
      4. Time Series Data
      5. Cross-Section Data
      6. Panel Data
      7. Data Volumes
   3. Data Dimensions and Attributes
      1. Data Attributes
      2. Data Dimensions
   4. Summary
4. 3. Data Quality Specifications
   1. Manufacturing Controls
   2. DQS Overview
   3. Data Quality Tolerances
      1. Completeness
      2. Timeliness
      3. Accuracy
      4. Precision
      5. Conformity
      6. Congruence
      7. Collection
      8. Cohesion
   4. Summary
5. 4. DQS Model Example
   1. Completeness DQS
   2. Timeliness DQS
   3. Accuracy DQS
   4. Precision DQS
   5. Conformity DQS
   6. Congruence DQS
   7. Collection DQS
      1. Example
   8. Cohesion DQS
      1. Example
   9. Fit for Purpose
   10. Summary
6. 5. Data Quality Metrics and Visualization
   1. Data Quality Metrics
   2. Data Quality Visualization
   3. Summary
7. 6. Operational Efficiency Cost Model
   1. Model Details
   2. Model Cost Assumptions
   3. Pre-Use Data Validations Versus Reconciliation
   4. Summary
8. 7. Data Governance
   1. Establishing a Data Governance Function
      1. Principles of Data Governance
      2. Data Governance Function
      3. Data Governance Models
   2. Creating a Data Governance Program
      1. Organizing the Program
      2. Establishing the Data Governance Council
      3. Engaging the Data Management Function
      4. Engaging Business Functions
      5. Enhanced Data Governance Operating Model
      6. Data Governance Program Activities and Deliverables
   3. Data Governance Business Value
   4. Data Management Maturity
   5. Summary
9. 8. Master Data Management
   1. Mastering Data
   2. Data Governance Synergies
   3. Data Management Synergies
   4. Summary
10. 9. Data Project Methodology
    1. Business Requirements
       1. Defining the Business Use Case
       2. Mapping Business Processes and Data Flows
       3. Impact Analysis
       4. Defining Data Quality Scorecards
       5. Data Usage Policies
    2. Technology Requirements
       1. Defining the Application Data Processing Use Case
       2. Mapping Application Functions and Data Flows
    3. Data Governance Requirements
       1. Data Definition Tasks
       2. Data Integrity Tasks
       3. Data Management Tasks
    4. Summary
11. 10. Enterprise Data Management
    1. Where to Begin?
    2. Understanding Data Volumes
    3. Engineering Data Quality
    4. Improving Efficiency
    5. Scaling Data Architectures and Pipelines
    6. Achieving a Data-Quality-First Culture
    7. Making It Happen
12. Index
13. About the Author