Every few years, a technology emerges that fundamentally changes how we think about data processing. MapReduce did it in 2004. Apache Spark did it in 2014. And after spending two decades building data pipelines across enterprises of every size, I’ve learned that the difference between a successful Spark implementation and a failed one rarely comes […]
Read more →Data Pipelines for LLM Training: Building Production ETL Systems
Building production ETL pipelines for LLM training is complex. After building pipelines processing 100TB+ of data, I’ve learned what works. Here’s the complete guide to building production data pipelines for LLM training. Figure 1: LLM Training Data Pipeline Architecture Why Production ETL Matters for LLM Training LLM training requires massive amounts of clean, processed data: […]
Read more →Tips and Tricks – Use Intersection Observer for Lazy Loading
Load images and content only when they enter the viewport for faster initial page loads.
Read more →Modern Python Patterns for Data Engineering: From Async Pipelines to Structural Pattern Matching
Introduction: Modern Python has evolved dramatically with features that transform how we build data engineering systems. This comprehensive guide explores advanced Python patterns including structural pattern matching, async/await for concurrent data processing, dataclasses and Pydantic for robust data validation, and context managers for resource management. After building production data pipelines across multiple organizations, I’ve found […]
Read more →Your Copilot Is Watching: The Real Story Behind AI Coding Assistants in 2025
Something shifted in how we write code over the past two years. It wasn’t a single announcement or product launch—it was the gradual realization that the cursor blinking in your IDE now has a silent partner. GitHub Copilot crossed 1.8 million paid subscribers in 2024. Cursor raised $60 million at a $400 million valuation. Amazon […]
Read more →Tips and Tricks – Use functools.cache for Automatic Memoization
Cache expensive function results automatically with the built-in cache decorator.
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