Zalando is rolling out Delta Sharing to give partners real-time, governed access to data. No more manual exports, just scalable interoperability across teams and systems.
What happens when cloud roles are over-permissioned and APIs aren't locked down? This post breaks down how enterprise networks become vulnerable through misconfigured Azure IAM. Eye-opening stuff for platform and infra teams.
A sharp, opinionated take that argues most AI agents are unreliable and overhyped. Instead of building fragile generalists, this piece urges you to focus on narrow, robust tooling.
One team ditched Kafka in favor of gRPC to reduce latency and simplify infra. A thoughtful case study that challenges default architectural choices.
An emerging role that blends engineering with metadata, usability, and making data discoverable. Think beyond pipelines.
Learn how to implement secure, role-based access control in Databricks down to the column and row level.
Give your GenAI systems real memory using Vertex AI and vector databases. This tutorial walks through building agents that remember context across sessions.
You can now reuse complex logic with parameterized TVFs directly in the DataFrame API. Write cleaner pipelines without losing SQL-style reusability.
David Meyer, SVP of Product, breaks down where Databricks is going next. From Lakehouse to AI-native tooling, this is a great listen for anyone working on next-gen data platforms.
This session explores how to scale GenAI workloads using GPU-optimized cloud setups. Learn how to balance speed, cost, and reliability with both hyperscalers and new AI-native providers.
Netflix introduces its Unified Data Architecture to power batch, streaming, and ML pipelines across a scalable and modular platform.
A new open-source Python notebook for building reactive dashboards with reproducible, modular code and minimal boilerplate.
Pinterest unified its ML stack using Ray to enable scalable training, hyperparameter tuning, and modular end-to-end pipelines.