Meta introduces a ranking system to improve notification relevance and cut noise, boosting user engagement and satisfaction.
Xebia explores why AI adoption fails, from data gaps to explainability issues, and how governance and transparency rebuild trust.
A practical guide to system design essentials like sharding, caching, CAP theorem, and queues, tailored for data engineers.
A quick breakdown of Parquet v1 vs v2, what changed, and why it matters for schema evolution and performance tuning.
Slack details how they automated anomaly detection and alerting to keep systems reliable at scale.
Booking.com shares real-world lessons for evaluating LLMs, from dataset design to balancing automated and human reviews.
A step-by-step look at moving a billion records between databases with phased cutovers and zero downtime.
Polars launches a managed cloud platform with distributed support, bringing Rust-powered performance to big data analytics.
Google’s Ryan Salva discusses how AI tools are reshaping developer experience, DevOps, and collaboration workflows.
A hands-on project building a production-ready ML pipeline with Astro and Apache Airflow.
HashiCorp’s license shift and IBM’s acquisition make Terraform’s future uncertain. OpenTofu, backed by the Linux Foundation, offers a safer, fully open alternative.
OLake replicates Postgres, MySQL, MongoDB, and Oracle to Apache Iceberg at up to 64K RPS, with CDC, schema discovery, and a lightweight Docker UI.
How to connect Azure DevOps with Power BI deployment pipelines using service principals, extensions, and YAML-based CI/CD.