Data Management: Page


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    Zilliz ups vector search results with Milvus database update

    Native access to data lakes and a new data retrieval engine highlight the latest release as the vendor competes for market share amid a crowded field.

    By • July 20, 2026
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    Expert Advice

    AI data fabric emerges as a governance layer for agents

    The latest take on data fabric architecture promises to help AI agents coexist with existing platforms, but there's some assembly required.

    By • July 17, 2026
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    How agentic AI amplifies data management challenges

    AI agents pose new data management challenges and magnify familiar ones. To build a solid agentic foundation, data leaders must plan for these critical challenges.

    By • July 16, 2026
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    Expert Advice

    Data ontologies are foundational for usable AI outputs

    Data ontologies strengthen AI outputs with governed definitions across platforms and departments, helping data leaders boost trust and improve decision-making.

    By • July 15, 2026
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    Regatta Data launches unified base for AI with RegattaDB

    The database vendor is entering a crowded market with the launch of a database purpose-built for agents by unifying disparate data workloads.

    By • July 15, 2026
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    How governance as code controls AI agent risk

    As more stringent EU AI Act requirements take effect, enterprises need runtime guardrails that control autonomous agents' actions, govern data access and preserve audit evidence.

    By • July 14, 2026
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    Alation launches OS for building, governing AI agents

    While not the first AI governance suite, the vendor's Intelligence Operating System is somewhat unique by unifying data, context and agents in one environment.

    By • July 14, 2026
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    Credit: Peter Dazeley via Getty Images
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    What a leadership transition reveals about your data strategy

    The failure pattern of a leadership transition reveals what data strategy institutionalization requires. Without it, a data strategy framework is a dependency, not a strategy.

    By Jelani Harper • July 9, 2026
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    How to use AI to enforce data governance policies

    AI models and agents can automate data governance policy enforcement for proactive governance in dynamic data environments. But don't forget the human element.

    By Anne Marie Smith, Ph.D. • July 9, 2026
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    AI agent failures offer hidden value for enterprises

    Most agent pilots will never reach production, but these failures can prove useful to data operations. Organizations should look to the 2010s mobile app boom for guidance.

    By • July 1, 2026
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    Why Apache Iceberg is the center of attention in data platforms

    In a Q&A, consultant Donald Farmer explains why vendors are rushing to support Apache Iceberg and discusses its capabilities and deployment issues for data teams.

    By • July 1, 2026
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    Securing data against AI attacks can’t be a side project

    The same AI capabilities that power enterprise innovation also give attackers machine-speed access to database vulnerabilities, demanding a shift in how organizations protect data.

    By • June 30, 2026
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    AI agents push enterprises toward unified data governance

    Enterprises facing data sprawl and growing risks from autonomous agents need unified governance and runtime controls to manage agent access and actions they can take.

    By • June 30, 2026
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    Couchbase evolution continues with new data layer for AI

    New capabilities including Agent Memory and extension to edge devices help the vendor compete for market share as it grows beyond its database roots.

    By • June 30, 2026
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    Latest MongoDB tools tackle top AI development hurdles

    New capabilities address the data retrieval accuracy and regulatory compliance issues that often stall initiatives, and could help distinguish the vendor from competitors.

    By • June 30, 2026
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    Agents are altering data security needs, Oracle responds

    Traditional strategies that protect infrastructure systems are not enough with agents autonomously accessing data and threat actors using AI to discover new vulnerabilities.

    By • June 24, 2026
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    Data modeling is having a moment, and AI is the reason

    Data modeling defines how enterprise data is structured and governed, and it has become the foundation for trustworthy AI, cloud migration and compliance.

    By • June 23, 2026
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    CData aims to simplify AI development with latest features

    New capabilities that reduce data integration tasks and connect data with AI aid developers while helping the vendor carve out a niche amid a competitive landscape.

    By • June 23, 2026
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    Latest EnterpriseDB features unify data for AI development

    New capabilities address the data sprawl that sometimes stops enterprises from successfully building agents and could help differentiate the vendor from competitors.

    By • June 23, 2026
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    Which data management costs should survive budget cuts?

    Tighter budgets force hard choices about data governance. This breakdown of essential data management costs shows where to cut spending and where cuts create risk.

    By Chris Tozzi • June 22, 2026
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    AWS latest to introduce context layer for agentic AI

    With context key to agents performing in production, the tech giant's latest new features aim to feed cutting-edge tools the situational awareness they require.

    By • June 17, 2026
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    Databricks intros new Genie, data management tools to aid AI

    Features address context for agents, readying data for AI, cost control, security and flexibility to help users overcome problems that prevent pilots from reaching production.

    By • June 17, 2026
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    8 data integration challenges and how to overcome them

    Data integration in modern architectures faces eight challenges, from preserving lineage at scale to serving AI and analytics workloads, each explored with practical strategies.

    By • June 15, 2026
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    Databricks intros OpenSharing, a new standard for sharing AI

    The open source protocol modernizes collaboration by enabling teams to share AI assets such as AI models and agent skills across domains and with external partners.

    By • June 11, 2026
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    Unstructured data needed, but often untapped, for agentic AI

    AI development initiatives hinge on the quality and completeness of the underlying data, but research from BARC shows that many organizations struggle to operationalize key data.

    By • June 8, 2026