Data Engineering Insights

Claude Models Explained: Which One Should You Use?

A beginner-friendly guide to the Claude model family. Learn what Haiku, Sonnet, Opus, and Fable 5 each do best, how they differ in speed and cost, and how to pick the right one for your project.

RAG Explained: Teaching AI to Search Before It Speaks

A beginner-friendly guide to Retrieval-Augmented Generation — how AI can search your documents before answering. Covers the full RAG pipeline, embeddings, vector databases, and how it compares to MCP.

MCP Explained: The Bridge Between AI and the Real World

A beginner-friendly guide to MCP, how AI models connect to databases, files, APIs, and real-world tools

LLM, RAG, MCP, or Agent — How to Pick the Right Architecture for AI in Data Engineering

Before you choose any AI technology — understand your project first. What does it need? What problem should AI solve? This article gives you a clear framework to decide which AI layer fits your data engineering project.

From Text to Thought: How RAG and MCP Are Changing the Way AI Works

Data Engineering Roadmap: How Every Data Engineer Should Start

A complete step-by-step roadmap for anyone who wants to become a data engineer — covering Python, SQL, cloud platforms, streaming, and Infrastructure as Code. Based on 20+ years of real industry experience.