Azure Data Services: Data Factory, Synapse, and Event Hubs
Build data pipelines on Azure with Data Factory, Synapse Analytics, and Event Hubs. Learn integration patterns, streaming setup, and data architecture.
Posts in technical
Backfills: Rebuilding Historical Data at Scale
Backfills reprocess historical data to fix bugs or load new sources. Learn strategies for running backfills safely without breaking production pipelines.
Backpressure Handling: Protecting Pipelines from Overload
Learn how to implement backpressure in data pipelines to prevent cascading failures, handle overload gracefully, and maintain system stability.
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.
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.