#Data Architecture
13 articles with this tag
Databricks Pushes Agentic AI with Lakebase
Databricks bolsters its Lakehouse platform with Lakebase and partner solutions to accelerate agentic AI development and data modernization.
AI Infrastructure: The Speed Problem
AI adoption is bottlenecked by slow, costly infrastructure. Companies need 'agentic speeds infrastructure' for autonomous AI to succeed.
Databricks Refines Partner Framework
Databricks updates its Partner Well-Architected Framework with AI-ready guidance, Dev Kit, and open-source Firefly to accelerate partner innovation.
Data Pipeline Architecture Explained
Understand the core layers, common patterns like ELT and Medallion, and best practices for building robust data pipelines.
Data Products Are Dead; Services Are In
The traditional data product model is failing businesses. Discover why data services are the future for scalable AI and rapid growth.
Databricks Fortifies Lakehouse Against Cloud Outages
Databricks is engineering its Lakehouse architecture for inherent resilience against cloud failures, using stateless compute and compartmentalization.
nOps Rebuilds Cloud Savings Platform on Databricks
nOps rebuilt its cloud cost optimization platform on Databricks Lakebase, integrating operational and analytical data for greater efficiency.
AI Agents Need a New Foundation
AI agents are ready, but most enterprise architectures aren't. Databricks argues for a foundational shift to transactional data infrastructure for true AI value.
Killing the Builder's Tax for AI Apps
Tech leaders are cutting development costs and speeding up AI deployment by unifying data and applications on a single platform.
AI Needs Faster Databases
AI demands real-time data. Traditional operational databases lag, but new 'lakebase' architectures are bridging the gap for faster, smarter AI.
AI Agents Need Context, Not Just Data
AI agents need real-time behavioral context, not just historical data, to make effective decisions. A robust customer context layer is key.
AI Agents Join the Org Chart
Snowflake outlines a new framework for AI integration, emphasizing unified data, business logic, and a 'hybrid' workforce of humans and AI agents.
The Semantic Layer: Data's Single Source of Truth
The semantic layer translates raw data into business meaning, ensuring consistency for BI and AI, with modern architectures embedding this logic directly into the data platform.