The article examines how JSON, once the universal data language for backend systems, is being pushed back from the interaction layer in AI‑driven applications, outlines its five key shortcomings, and explores emerging alternatives such as natural‑language interfaces, Markdown, YAML, and function calling.
The article explains the three core data categories—structured, semi‑structured, and unstructured—illustrates their characteristics with real manufacturing examples, compares suitable storage and processing tools, and outlines three practical principles for effective data integration and governance.
The article explains the definitions and practical differences of structured, semi‑structured, and unstructured data, compares suitable storage and processing technologies, discusses governance challenges, and offers a step‑by‑step strategy—including a data‑integration tool example—to help IoT projects select the optimal data architecture.
Apache Doris 3.0 introduces storage‑compute separation, native lakehouse write‑back, optimized Variant handling for semi‑structured data, stronger ETL transaction support, enhanced multi‑table materialized views, and Java UDTF capabilities, providing developers with more flexible, cost‑effective, and high‑performance analytics solutions.
This tutorial demonstrates how to build an advanced Retrieval‑Augmented Generation (RAG) system for semi‑structured PDF data by leveraging LangChain, the unstructured library, ChromaDB vector store, and OpenAI models, covering installation, PDF partitioning, element classification, summarization, and query execution.
This article explains the nature of semi‑structured data, compares traditional schema‑on‑read and schema‑on‑write approaches, and details MaxCompute's columnar storage solution that balances flexibility, performance, and cost for large‑scale data warehouses.
This article explains the nature of semi‑structured data, compares schema‑on‑read and schema‑on‑write approaches, and shows how Alibaba Cloud MaxCompute leverages columnar storage and dynamic parsing to achieve low‑cost, high‑performance analytics for large‑scale data workloads.
This article explains the concepts of semi‑structured data, compares traditional schema‑on‑read and schema‑on‑write approaches, and details MaxCompute's columnar storage solution—including AliORC, adaptive query processing, and handling of dirty or sparse data—to achieve high performance and low cost in big‑data warehousing.
