Data Engineering

February 20, 2026 at 02:41 PM | Est. read time: 10 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Modern analytics stacks rarely live in one place. A single dashboard might need customer attributes from a data warehouse, clickstream events from a data lake, and subscription data from an […]

February 20, 2026 at 03:21 PM | Est. read time: 9 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Modern products live and die by what they know right now: fraud signals, IoT telemetry, clickstream behavior, logistics updates, pricing changes, and application health metrics. Batch pipelines can’t keep up

February 19, 2026 at 02:13 PM | Est. read time: 10 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Modern data stacks move fast: new pipelines ship weekly, dashboards multiply, and “who changed what?” becomes a daily question. The problem isn’t that organizations lack data-it’s that they lack trust

February 18, 2026 at 01:33 PM | Est. read time: 11 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Modern data platforms move fast: new pipelines, new storage layers, new compute clusters, tighter security requirements, and constant cost pressure. If your infrastructure is still built by clicking around in

February 16, 2026 at 03:27 PM | Est. read time: 10 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Real-time applications live and die by latency, throughput, and how quickly you can turn fast-moving events into decisions. Two popular technologies often considered for these systems are Redis (an in-memory

February 13, 2026 at 03:52 PM | Est. read time: 10 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Choosing a database isn’t just a technical checkbox-it shapes your product’s performance, scalability, developer experience, and long-term costs. If you’re comparing PostgreSQL vs MongoDB vs DynamoDB, you’re likely building something

February 13, 2026 at 03:54 PM | Est. read time: 11 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Database choices often feel “technical” and therefore easy to postpone-or delegate without much oversight. But in practice, database decisions are business decisions. They shape performance, reliability, security, reporting, delivery speed,

February 12, 2026 at 02:28 PM | Est. read time: 11 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Machine learning teams often hit the same wall: it’s not the model that’s hard-it’s everything around it. Reproducibility, experiment tracking, consistent deployments, automated retraining, monitoring, and governance quickly become the

February 12, 2026 at 04:13 PM | Est. read time: 10 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Vector databases have quickly become a foundational piece of modern AI-especially if you’re building applications powered by semantic search, recommendation systems, RAG (Retrieval-Augmented Generation), or LLM chatbots over private data.

February 04, 2026 at 12:17 PM | Est. read time: 10 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Modern analytics and AI projects live or die by data movement. You can have a best‑in‑class warehouse, a solid BI layer, and a high-performing ML stack-and still struggle if your