Learn how developers can use data agents for natural-language querying, Copilot Studio for AI interactions, and real-time intelligence for streaming analytics.
Optimize Spark jobs by tuning configurations, writing efficient code (Data Frames, broadcast joins), using optimized storage, and monitoring the Spark UI and logs.
Synthetic data lets quants stress-test equity strategies beyond noisy markets, preserving volatility, and building resilience before risking real capital.
This article explores the challenges faced, the solutions adopted, and the prospects for further improving the process. The rules vary depending on the guidelines.
In this article, I have demonstrated how Iceberg Data can be accessed through the Iceberg REST Catalog from Data Mesh with a simple Python application.
An introductory tutorial for Java developers on writing AI-infused applications using Quarkus with LangChain4j. You don't need Python to write AI apps.
JNI is powerful but tricky. Automate boilerplate with generators, carefully manage references, test with CheckJNI, and embrace the chaos; it gets satisfying.
Spring AI agentic patterns show how to coordinate multiple ChatClient calls to LLMs. We look at how Dapr Workflows can make these interactions durable and resilient.
Learn why using Postman's 'Fix test' may mask bugs — tips to investigate failures, preserve test intent, and protect API reliability. Verify, then act.