Databricks Enters Cybersecurity Market With Lakewatch SIEM Platform

Databricks is stepping into the cybersecurity space with Lakewatch, an agentic SIEM platform designed to run on top of its lakehouse architecture and extend it into security operations. Lakewatch is available in private preview. With this move, the San Francisco-based company is positioning its lakehouse as a central control layer for enterprise data. The move…

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Spec-Driven Development: The Key to Protecting AI-Generated Data Products

The most dangerous data problems don’t trigger alerts or cause catastrophic failures. They look fine on the surface until the business realizes the damage they’ve done. AI-assisted development has increased in popularity, however, and this approach is only making the problem worse. Consider a dashboard built for workforce capacity planning. The person building the tool…

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Snowflake Pushes Into Agentic AI with Project SnowWork

Snowflake is pushing further into the agentic AI trend with the launch of Project SnowWork, a new platform meant to help enterprises move beyond data analysis and into execution, with much of the work handled autonomously. With SnowWork, the aim is to go beyond dashboards and generated answers to automate the next steps, allowing business…

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AI-Native Assistants Have Arrived—But Earning Trust Is the True Innovation

Artificial intelligence has dazzled us with conversation. The real revolution is underway, one where AI doesn’t just talk, but acts. Across large organizations, a new class of AI-native assistants is quietly reshaping workflows. These systems go beyond chat; they take action. They process claims, open support tickets, reroute supply chains, and even draft contracts, all…

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Snowflake Report Finds GenAI Paying Off for Enterprises Despite Data Challenges

The latest Snowflake report titled “The ROI of Gen AI and Agents” shows that GenAI seems to be working quite well in the enterprise setting – contrary to other reports that either point to feverish hype or stubborn skepticism. An overwhelming 92% of early adopters say they are seeing positive returns from the GenAI investments. …

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Beyond the Hype: 5 Surprising Realities of Enterprise AI

The AI fatigue that defined the late 2023 and 2024 business cycles was, in hindsight, a necessary correction. During that period, many organizations found themselves trapped in what industry observers called “pilot purgatory.” Millions were poured into experimental generative AI pilots, comprised mostly of chatbots designed to summarize meetings or draft internal emails. While these…

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MariaDB to Acquire GridGain to Tackle the AI Latency Gap

MariaDB is set to acquire GridGain Systems with the aim to deliver sub-millisecond data performance for agentic AI workloads. GridGain is the company behind the in-memory computing platform and developer of the open source project Apache Ignite. The deal comes at a time when technology vendors are rethinking the foundations of the modern data stack…

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Real World Lessons On Reliable Data Movement At Global Scale

Moving large-scale data across platforms, clouds, and global regions is no longer a special project for a few highly technical teams. It has become a routine operational requirement for modern enterprises. Companies now run analytics in one environment, store long-term archives in another, and build applications that must pull data from multiple locations with accuracy…

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The End of the ‘Observability Tax’: Why Enterprises are Pivoting to OpenTelemetry

As enterprises scale AI, they are inadvertently worsening an existing data crisis. The resulting surge in telemetry is overwhelming infrastructure already strained by the shift to multi-cloud environments, applications, and IoT, which is driving inflated costs. Organizations are paying for the collection, storage, and processing of massive data logs that often provide little business value….

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Confluent Extends Its Reach Up the AI Stack With Agent2Agent Support

The conversation around AI agents has focused heavily on reasoning. Less attention has gone to coordination. Enterprises that have been experimenting with agents are struggling to manage agents that share context and operate across live business systems without stepping on each other. Running a single agent on streaming data is manageable. Running several agents across…

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