Data Quality, Governance & Observability Roadmap — Step-by-step Learn…
Ensuring data is trustworthy, discoverable and compliant: data quality testing, lineage, cataloging, privacy and observability practices
The Data Quality, Governance & Observability roadmap
- Data Quality and Governance Fundamentals — beginner
- Why Data Quality and Governance Matter — beginner
- Data Quality vs Data Governance vs Data Observability — beginner
- The Cost of Bad Data — beginner
- Where This Work Sits in a Data Organization — beginner
- The Modern Data Quality and Governance Tool Landscape — beginner
- Setting Up Basic Data Quality Checks — beginner
- Dimensions of Data Quality — beginner
- Dimensions of Data Quality — beginner
- Accuracy and Validity Checks — beginner
- Completeness and Consistency Checks — beginner
- Timeliness and Freshness as Quality Dimensions — beginner
- Defining Quality Expectations for a Dataset — beginner
- Data Quality Testing Techniques — beginner
- Writing Data Quality Tests — beginner
- Statistical Data Quality Checks — beginner
- Referential Integrity Testing — beginner
- Testing Data Quality at Different Pipeline Stages — beginner
- Balancing Test Coverage with Maintenance Burden — beginner
- Data Quality Frameworks and Tools — beginner
- Great Expectations Fundamentals — beginner
- Soda and dbt-Based Quality Tools — beginner
- Commercial Data Observability Platforms — beginner
- Choosing a Data Quality Framework — beginner
- Integrating Quality Checks into Existing Pipelines — beginner
- Data Quality Monitoring — beginner
- Continuous Data Quality Monitoring — beginner
- Data Quality Dashboards — beginner
- Alerting on Data Quality Issues — beginner
- Quality Scores and Data Health Metrics — beginner
- Data Quality SLAs — beginner
- Case Study: Building a Data Quality Program from Scratch — beginner
- Anomaly Detection for Data — beginner
- Anomaly Detection Fundamentals for Data — beginner
- Statistical Methods for Anomaly Detection — beginner
- ML-Based Anomaly Detection for Data Pipelines — beginner
- Reducing False Positives in Data Anomaly Alerts — beginner
- Anomaly Detection Across Pipeline Stages — beginner
- Data Freshness and SLAs — beginner
- Defining Data Freshness Requirements — beginner
- Monitoring Data Freshness — beginner
- Freshness SLAs and Escalation — beginner
- Balancing Freshness Against Pipeline Cost — beginner
- Communicating Freshness to Data Consumers — beginner
- Root Cause Analysis for Data Issues — beginner
- Root Cause Analysis Fundamentals for Data Issues — beginner
- Using Lineage to Debug Data Issues — beginner
- Common Root Causes of Data Quality Problems — beginner
- Incident Response for Data Quality Issues — beginner
- Postmortems for Data Quality Incidents — beginner
- Data Lineage — beginner
- Data Lineage Fundamentals — beginner
- Table-Level vs Column-Level Lineage — beginner
- Automated Lineage Extraction — beginner
- Lineage Tools and Platforms — beginner
- Using Lineage for Impact Analysis — beginner
- Visualizing Complex Lineage Graphs — beginner
- Data Cataloging and Discovery — beginner
- Data Catalog Fundamentals — beginner
- Choosing a Data Catalog Tool — beginner
- Populating and Maintaining a Catalog — beginner
- Search and Discovery in a Data Catalog — beginner
- Driving Catalog Adoption Across an Organization — beginner
- Metadata Management — beginner
- Metadata Management Fundamentals — beginner
- Business Glossaries — beginner
- Automated Metadata Harvesting — beginner
- Metadata Standards and Interoperability — beginner
- Metadata Quality and Governance — beginner
- Data Classification and Sensitivity — beginner
- Data Classification Fundamentals — beginner
- Identifying PII and Sensitive Data — beginner
- Automated Data Classification Tools — beginner
- Classification-Driven Access Policies — beginner
- Maintaining Classification as Data Evolves — beginner
- Privacy and Compliance — beginner
- Privacy Regulations Overview (GDPR, CCPA) — beginner
- Data Subject Rights and Their Technical Implications — beginner
- Data Retention Policies — beginner
- Data Minimization Principles — beginner
- Consent Management in Data Pipelines — beginner
- Privacy Impact Assessments — beginner
- Access Governance — beginner
- Access Governance Fundamentals — beginner
- Data Access Request Workflows — beginner
- Periodic Access Reviews — beginner
- Data Masking and Anonymization — beginner
- Row-Level and Column-Level Security — beginner
- Data Governance Frameworks and Programs — beginner
- Data Governance Program Fundamentals — beginner
- Data Governance Frameworks (DAMA-DMBOK and Others) — beginner
- Data Stewardship Roles — beginner
- Governance Councils and Decision-Making — beginner
- Measuring Governance Program Maturity — beginner
- Data Contracts and Ownership — beginner
- Data Contracts Fundamentals — beginner
- Designing and Enforcing Data Contracts — beginner
- Data Product Thinking — beginner
- Data Ownership Models — beginner
- Data Mesh Principles — beginner
- Career and Capstone — advanced
- Data Governance and Quality Career Paths — beginner
- Breaking Into Data Quality and Governance Roles — beginner
- Resume and Interview Prep for Data Governance Roles — beginner
- Case Study: Building a Data Governance Program — beginner
- Staying Current with Privacy Regulation and Tooling — beginner
- Capstone: Design a Complete Data Quality and Governance Program — beginner