AI Briefing#data-platform
The latest AI and developer news about #data-platform, with the original source and a short summary.
The latest AI and developer news about #data-platform, with the original source and a short summary.
It processes over 1 billion messages per day to provide product information optimized for presentation screens.
The system wraps deterministic processes in AI to extract errors and provide focused diagnosis, replacing legacy regex rules that left 50% of failures unclassified.
The platform reduces metric creation time from weeks to 1–2 hours and supports over 98% of experimentation metrics.
Data integration across three subsidiaries including GS Power enables approximately 690 users to access data via catalog subscriptions
kt cloud is building an AIOps model that connects scattered cloud data to support AI-driven operational decision-making.
Databricks announced an Agentic Data strategy that extends the Lakehouse so AI Agents can understand and act on enterprise business context.
Databricks presented an Agentic Data architecture designed to help AI Agents understand business context and perform tasks in real time.
This covers the operational and design challenges LY Corporation faced while integrating 1EB-scale HDFS clusters with different architectures.
To address the complexity of managing data assets, Netflix introduced Data Projects, a unified management system organized around projects rather than individual asset units.
Toss Place connects metric analysis to execution through Metric Review.
SK Planet is building AI competitiveness through service and data optimization rather than developing its own LLM.
Banksalad switched its Spark computing environment from EMR to Kubernetes, reducing operating costs by about 45%.
Coupang built a low-code, no-code workflow that automates data building and service development.
It is being developed and operated in-house with five components to resolve issues of external solution costs and functional limitations.
Based on the Kakao Winter Internship briefing, this summarizes the scope of work and hiring criteria for DB and Hadoop engineering roles.
Banksalad's data engineers are focusing on a data serving service that turns insights gathered through the data platform into APIs.
We operate an internal SaaS platform that supports the entire process from data collection to ML/AI utilization for Kakao crew members.
The Kakao Recommendation Team processes 1.7 billion recommendation requests daily across 15 services within 30–50ms, focusing on long-term service growth centered on revisit rates while enhancing technical accessibility through SaaSification and open-source releases.
Kakao's Ad Recommendation Team shared operational insights on 'Genesis', a Kafka Connect-based ETL platform, and open-sourced 'kafka-connect-web', a web tool for pipeline management.
Banksalad presented a MyData map and utilization strategy that connects data across all industries, going beyond finance.