Apache Spark 4.1 is here. Discover how Real-Time Mode (RTM), Declarative Pipelines, and Arrow-Native UDFs are transforming data engineering and PySpark performance
Apache Spark 4.1 is Here: The Next Chapter in Unified Analytics Read More »
Learn the difference between data processing guarantees (At-Most-Once, At-Least-Once, Exactly-Once) with simple real-world examples. Perfect for data engineering beginners
Data Processing Guarantees Explained: Exactly-Once, At-Least-Once, and At-Most-Once Read More »
2025 marked the shift from experimenting with AI to relying on it. In this retrospective, I explore how AI killed the ‘tedious task’ but failed the ‘context test’—specifically sharing why OpenAI, Claude, and Gemini all couldn’t fix a complex protoc dependency that still required a human engineer.
2025 Retrospective: How AI Changed the Way I Engineer Read More »
The ultimate guide to Apache Spark. Learn performance tuning with PySpark examples, fix common issues like data skew, and explore new Spark 4.0 features.
Struggling with late or out-of-order data? Learn how Apache Flink Watermarks work with event time to build accurate, reliable real-time stream processing systems.
What Are Apache Flink Watermarks? A Beginner’s Guide to Handling Late Arrival Data Read More »
Stay current with the essential data engineering news from June 2025. This monthly roundup covers the biggest announcements from Databricks’ Data + AI Summit, new Snowflake features, Apache Flink updates, and the growing role of AI and Apache Iceberg in the data landscape.
Data Engineering Heats Up in June 2025: A Look at the Latest Developments Read More »
Learn how to build a powerful, low-cost AI social media scheduler using n8n and DeepSeek. Automate content creation, shorten links, and schedule Twitter posts—without paying for Buffer, Hootsuite, or ChatGPT
Automate Social Media Like a Pro (Almost Free): Using n8n + DeepSeek AI Read More »
Looking for the best books on data analytics and AI agents? Discover top-rated titles with summaries, user reviews, and expert recommendations for every data enthusiast and AI innovator.
10 Best Books on Data Analytics with AI Agents – Read Before You Build! Read More »
Learn how to avoid 10 common data engineering pitfalls—like Spark data skew, Airflow retry chaos, schema drift, and more—with practical solutions
Don’t Get Tripped Up! 10 Common Data Engineering Pitfalls Read More »
Learn how LLM + MCP synergy revolutionizes complex tasks. An Apache Airflow 3.0 case study demonstrates auto-updating DAGs and overcoming AI limitations.
