Insights in Software, Data, and AI

Supabase vs Firebase: compare Postgres SQL vs Firestore NoSQL, auth, real-time, storage, and functions, plus when to choose each for your app.

Why data transformations fail: vague goals, poor data quality, weak ownership and adoption. Learn how to make your data transformation stick.

Move beyond dashboards: learn decision automation with AI, rules, and real-time data to turn insights into actions faster across modern teams.

Monitor LLM hallucinations in production: practical metrics, evaluation methods, and feedback loops to build safer, more reliable AI applications.

Data platform migration timelines explained. See what affects duration, phases, and tips to reduce risk and delays.

Build a lakehouse architecture from scratch with a practical blueprint for modern analytics and AI-Delta Lake/Iceberg, governance, pitfalls, and steps.

Scale AI apps without runaway cloud bills. Learn cost drivers, efficient architecture, and optimization tactics for scalable, cost-effective AI inference.

Kafka topic design best practices to avoid bottlenecks-prevent hot partitions, cut consumer lag, and keep Kafka throughput predictable as you scale.

Learn how to build data agents that communicate with each other. Discover architectures, protocols, and patterns for scalable AI operations in 2026.