Data Engineering

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Series Overview Answer-first: This series details enterprise AI data pipeline engineering, covering GraphRAG, multimodal document ingestion, late chunking, streaming CDC, and vLLM inference. No matter how sophisticated the Prompts or how smooth the UI of an AI/Agentic system is, it will still “hallucinate” if the underlying data is garbage. In 2026, Naive RAG (simply chunking text and throwing it into a Vector Database) is dead for complex enterprise problems. Instead, we must solve the difficult challenges of Data Engineering: processing millions of pages of unstructured documents (PDFs, tables, diagrams), linking them into a Knowledge Graph (GraphRAG), maintaining Role-Based Access Control (RBAC), and continuously measuring accuracy (Evals). ...