Data Management
Data Management on Beyond Market Intelligence: a running collection of 2 stories we have gathered and hand-picked because they are worth your time. Every post here touches on data management in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around data management, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.

Many Companies Use AI. Few Know How to Build an AI-Native Enterprise Data Platform.
Many companies are leveraging AI, yet few possess a practical architecture for an AI-native enterprise data platform. Building one demands more than isolated AI tools; it requires a cohesive system. Our latest article explores a robust architecture featuring data agents for streamlined integration, AI-powered quality assurance, and essential AI governance. Discover how to move beyond experimentation and establish a foundation for scalable, reliable AI initiatives. For related insights on structuring data for AI agents, see Pinecone’s introduction of Nexus Engine.

How Uber Builds Zone-Failure-Resilient OpenSearch Clusters
Maintaining operational resilience is paramount, and Uber’s approach to zone-failure-resistant OpenSearch clusters exemplifies this. Claudio Masolo details how Uber ensures continuous query and ingestion capabilities even during zone outages, leveraging OpenSearch's shard allocation and a proprietary isolation-group system built on Odin. This innovative architecture delivers a robust foundation for data-driven decision-making. For further insights into the challenges of AI agent evaluation, explore our related article, "The agent evaluation gap."