Data-Centric AI: why more data doesn't mean better models
The paradigm shift in machine learning: invest in data quality, not bigger models. Tools and practices to implement it.
The paradigm shift in machine learning: invest in data quality, not bigger models. Tools and practices to implement it.
DevOps revolutionized software development. DataOps is doing the same for data. Practical guide with tools and real cases.
The story of how I went from a stuck analyst making reports to actually understanding how data works. And why you should consider it.
Most dashboards are corporate theater. Decisions are made by gut feeling and justified with data afterwards.
What a Data Engineer is, what tools they use, what the real day-to-day looks like, and how to start if you come from Excel/Power BI.
Why companies buy AI without having their data ready. The data plumbing problem.
Unified data architecture regardless of where data lives. What it means for a data engineer and how it relates to tools you already use.