Data Engineering

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

February 02, 2026 at 01:24 PM | Est. read time: 11 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Modern businesses don’t just store data-they move it. Customer clicks, payments, IoT telemetry, application logs, and operational events are generated continuously, and teams increasingly need those signals in real time

January 29, 2026 at 04:30 PM | Est. read time: 15 min By Valentina Vianna Community manager and producer of specialized marketing content Modern data architecture isn’t just an IT topic-it increasingly shapes speed to market, customer experience, operational efficiency, and compliance risk. The way your company collects, governs, shares, and uses data determines whether

January 30, 2026 at 01:34 PM | Est. read time: 11 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Data Mesh has become one of the most talked-about approaches in modern data architecture-and for good reason. It promises faster delivery of data products, better alignment between data and business

January 30, 2026 at 01:30 PM | Est. read time: 10 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Modern data teams are under pressure to do everything at once: power dashboards, support ad hoc analysis, run machine learning, and keep governance airtight-all while costs and complexity keep rising.

January 29, 2026 at 02:34 PM | Est. read time: 12 min By Valentina Vianna Community manager and producer of specialized marketing content Choosing between Snowflake and Databricks isn’t just a “data warehouse vs data lakehouse” debate anymore. Both platforms have expanded aggressively, and the real decision often comes down to technical architecture choices that

January 29, 2026 at 02:00 PM | Est. read time: 12 min By Valentina Vianna Community manager and producer of specialized marketing content Data engineering keeps evolving fast-but the difference between “experienced” and “senior” is becoming clearer every year. In 2026, it’s not just about building pipelines or knowing a handful of tools. Senior data

January 26, 2026 at 02:28 PM | Est. read time: 12 min By Valentina Vianna Community manager and producer of specialized marketing content Modern data and AI systems don’t run on “one-off scripts” for long. As soon as you have multiple sources, dependencies, schedules, retries, and stakeholders who expect consistent results, you need a workflow