Expert Advice

Practical guidance from industry experts on Data


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    How to evaluate the leading data fabric tools and platforms

    AI has increased the importance of connecting distributed data. Data leaders should evaluate whether these data fabric vendors offer reliable access while maintaining control.

    George Lawton • Oct. 9, 2026
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    How to control agentic AI access to enterprise data

    AI agents stand in for users and reach multiple systems. Governing their access requires distinct identities, scoped authority and records that show who authorized each action.

    Sean Kerner • Sept. 21, 2026
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    How much does conversational analytics cost in 2026?

    Early estimates will often cover the technology but miss much of the added work. Expenses often rise as organizations prepare the platform for wider, reliable enterprise use.

    George Lawton • Sept. 10, 2026
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    How to verify the value of AI-powered business analytics

    Executives can separate AI analytics capabilities from marketing hype by taking steps to confirm the platform improves decision-making and gives results that hold up.

    Damon Garn • Sept. 9, 2026
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    How CDOs can show the business impact of data

    CDOs can defend the spend on data programs by tying outcomes to saved time, lower risk, revenue gains and AI projects that reach production.

    Donald Farmer • Aug. 19, 2026
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    7 expert recommended data observability tools

    Commercial data observability tools can offer organizations pre-built components and plenty of vendor support for data use cases including monitoring, security and decision-making.

    George Lawton • Aug. 18, 2026
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    Integrate structured and unstructured data for better AI outputs

    For AI agents to give the most accurate, informed responses, organizations must provide them with all the facts. Even those that are hidden in an old email or customer claim.

    Sean Kerner • July 31, 2026
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    Is your data infrastructure ready for the zettabyte era?

    AI initiatives are driving demand for curated, controlled data. Leaders must move beyond capacity planning and build the governance and quality practices that make data usable.

    Brien Posey • July 29, 2026
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    Business resilience vs. business continuity: Key differences

    Business continuity and resilience go hand in hand and play a role in an organization's disaster recovery plan. Essentially, business continuity is needed to achieve resilience.

    Paul Kirvan and Rosa Heaton • July 29, 2026
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    Modern IT threats demand continuous resilience

    Continuous resilience enables organizations to anticipate, withstand and recover from disruption. Modernize today to reduce operational risk and improve business agility.

    Damon Garn • July 28, 2026
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    How data mesh supports AI-ready data architectures

    Data mesh can improve data access for AI initiatives by decentralizing ownership and governance, but it doesn't solve every data challenge.

    Chris Tozzi • July 24, 2026
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    The 5 pillars of data observability

    Data observability provides complete oversight of an organization's data pipeline. Use the 5 pillars of data observability to ensure efficient, accurate data operations.

    Erin Sullivan, Peter Spotts • July 24, 2026
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    CDO challenges that hinder data-driven initiatives

    Chief data officers must turn AI ambition into measurable value. These eight issues show where data strategies break down -- and how leaders can respond.

    Mary Pratt • July 22, 2026
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    How AI is changing data protection

    There's no doubt that recent AI developments have affected data protection. IT leaders must not only stay on top of these changes but also prepare for what's next.

    Sean Kerner • July 21, 2026
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    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.

    John Moore • July 17, 2026
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    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.

    Sean Kerner • 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.

    Sean Kerner • July 14, 2026
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    4 AI incidents that harmed resilience efforts

    AI can be a helpful tool when users respect its limitations and verify what it claims to be fact. If not, the impact on the organization can be catastrophic.

    Stuart Burns • July 10, 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.

    Anne Marie Smith, Ph.D. • July 9, 2026
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    The board-level economics of downtime

    Downtime is an organization-wide issue. Leaders who treat resilience as a strategic capability are better positioned to navigate future operational, cyber and market disruptions.

    Damon Garn • July 7, 2026
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    Isolated recovery environments are critical for modern DR

    There is no room for error in disaster recovery, especially when it comes to backups. To ensure you’re recovering from a clean backup, consider an isolated recovery environment.

    Brien Posey • June 25, 2026
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    Why a dashboard audit matters before BI cleanup

    Managing large BI estates takes more than deleting stale dashboards. To keep order, leaders need to assess analytics usage and assign ownership to prevent clutter from returning.

    Mary Pratt • June 12, 2026
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    What zero-trust data protection means for business

    Implementing zero trust at the network level isn’t enough in today’s digital landscape, where critical business data is stored across platforms, applications and devices.

    Jacob Roundy • June 9, 2026
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    Why backup alone doesn’t guarantee cloud recovery readiness

    Successful backup jobs can still leave dependency and configuration gaps, making orchestration and recovery testing critical for restoring cloud services and SaaS apps.

    Sean Kerner • June 5, 2026
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    The data backup confidence gap: Are you really recovery ready?

    False confidence in data backups is a growing issue. IT leadership must ensure that recovery goals match backup realities to avoid extended downtime and loss of customer trust.

    Jacob Roundy • June 4, 2026