Data Lake

Key Takeaways Most people researching data lake architecture are trying to answer one question: How do we get analytics and AI value without creating a data swamp? A modern data lake is not only storage and compute. Mature solutions include metadata management, security, and governance. (Microsoft) Cloud architectures increasingly unify data with governance and catalog […]

Let me share something I’ve been thinking about lately—the shift from viewing data lakes as massive storage repositories to understanding them as active foundations for composed data products. It’s a transformation that’s reshaping how organizations actually use their data. My colleague Haricharuan recently wrote a good blog on the fundamental foundations of data products: Data […]

Most organizations rarely lack data, yet we often hear data leaders say, “We manage petabytes of data, yet arriving at an accurate insight is time-consuming.” Most data teams aren’t lacking in data; they lack reliable, reusable outputs. The signs are everywhere: high costs, slower processes, inaccurate insights, duplicated efforts, and a cluttered dashboard. Without curated, […]

Data lakes and modern data platforms promise the ability to ingest, process, and store massive volumes of unstructured, semi-structured, and structured datasets in a unified, centralized repository. However, in scenarios where projects and teams lack clear objectives and comprehensive implementation planning, the investments can soon turn into very expensive project failures. This blog discusses how […]