Change Data Capture: Real-Time Database Tracking with CDC
CDC tracks database changes and streams them to downstream systems. Learn how Debezium, log-based CDC, and trigger-based approaches work.
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Data Catalog: Organizing and Discovering Data Assets
A data catalog is the single source of truth for data metadata. Learn how catalogs work, what they manage, and how to choose one.
Data Contracts: Establishing Reliable Data Agreements
Learn how to implement data contracts between data producers and consumers to ensure quality, availability, and accountability.
Data Formats: JSON, CSV, Parquet, Avro, and ORC Explained
Compare data formats — JSON, CSV, Parquet, Avro, and ORC — covering structure, compression, schema handling, and when to use each in pipelines.
Data Governance: Practical Implementation Guide
Learn the essential framework for data governance including data ownership, quality standards, policy enforcement, and organizational alignment.
Data Lake Architecture: Raw Data Storage at Scale
Learn how data lakes store raw data at scale for machine learning and analytics, and the patterns that prevent data swamps.
Data Lineage: Tracing the Journey of Your Data
Learn how to implement data lineage for tracking data flow across systems, enabling impact analysis, debugging, and compliance.
Data Migration: Strategies and Patterns for Moving Data
Learn proven strategies for migrating data between systems with minimal downtime. Covers bulk migration, CDC patterns, validation, and rollback.
Data Quality: Validation, Monitoring, and Governance
Data quality determines whether pipeline outputs are trustworthy. Learn how to define rules, implement validation, and catch bad data before it reaches users.
Data Validation: Ensuring Reliability in Data Pipelines
Learn data validation techniques for catching errors early, defining constraints, and building reliable production data pipelines.