AI Trust Supported by Governance: Notes from DAMA NYC Data Day

Jim Barker recaps DAMA NYC 2026.

What Does a Chief AI Officer Do?

A breakdown of the role and responsibilities.

Critical Metrics for AI Trust

Learn the key metrics for AI trust across evolving, agent-driven AI systems.

The Data + AI Iceberg: What's Below the Surface

The eleven foundational disciplines that sit below the waterline.

The State of 'State of AI' Reports in 2026

A running list of major AI reports published in 2026.

Your AI Agents are Organizationally Blind. Lineage and Context Can Fix That.

AI agents don't know which data to trust, until you teach them.

Thought leadership

AI in Financial Services: How the Largest Institutions Are Using it Right Now

How financial services is deploying AI at enterprise scale.

Thought leadership

CDO and CISO: The Relationship That Makes or Breaks Enterprise AI Rollouts

The real blocker isn't what (or who) you think it is.

Thought leadership

The AI Data Readiness Model

Four capabilities. Five stages. One clear picture.

Thought leadership

The Enterprise AI Stack, Explained

A simple guide of the enterprise AI stack.

Thought leadership

AI in the Energy Sector: Oil and Gas, Utilities, and Renewables

Where the energy sector is using AI at enterprise scale.

Thought leadership

The Relationship Between Data Quality and AI Trust

Data quality alone doesn't produce AI trust.

Thought leadership

AI Terms Every Enterprise Data Team Needs to Know

54 AI terms every enterprise data team needs to know.

Thought leadership

The House of Data Series: People & Leadership

Thought leadership

Data Trust vs. AI Trust: What's the Difference?

Understand the key differences between data trust and AI trust.

Thought leadership

The House of Data Series: Data Literacy

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Trustworthy AI: What It Means and Why It's Important

What trustworthy AI means, and what it requires.

Thought leadership

The House of Data Series: Data Consumption

Thought leadership

We're Launching The AI Trust Summit

The AI Trust Summit in 2026 will bring together the leaders solving the biggest AI challenges.

Thought leadership

Responsible AI: Principles and Why It's Important

What responsible AI looks like for enterprises.

Day Three Dispatch: Gartner Data & Analytics Summit 2026

The theme of Day Three? Adaptability.

Thought leadership

The House of Data Series: Enablement

Thought leadership

Day Two Dispatch: Gartner Data & Analytics Summit 2026

The silent threats threatening to derail enterprise AI initiatives.

Thought leadership

Day One Dispatch: Gartner Data & Analytics Summit 2026

Four key themes and where to get started.

Thought leadership

Why Data Reliability Needs An Operating Model (Not More Alerts)

Gaurav Rastogi shares a smarter model for scaling data trust.

Thought leadership

The House of Data Series: Compliance

Product

How Lineage Works: A Bigeye Product Walkthrough

How end-to-end data lineage works within Bigeye.

Product

Introducing: Lineage for Financial Services

Audit-ready lineage for financial services.

Thought leadership

The House of Data Series: DataOps

Thought leadership

The 5 Reliability Metrics Every CDO Must Improve Quarterly

A quarterly data reliability report card.

Company

Onsites and Remote Life: Swimming Together While We Work Apart

Balancing remote work, distributed teams, and in-person bonding time.

Product

Architecting AI Trust: The Role of Sensitive Data Scanning

Sensitive Data Scanning powers AI-safe access to enterprise data.

Thought leadership

Webinar Recap: Insights from 400+ Enterprise AI Initiatives

A quick recap of our top takeaways.

Thought leadership

The House of Data Series: Data Security

Thought leadership

Webinar Replay: Insights from 400+ Enterprise AI Initiatives

What the data reveals in 2026.

Thought leadership

The House Of Data Series: Data Privacy

Product

How Sensitive Data Scanning Works: A Bigeye Product Walkthrough

How and when to use Sensitive Data Scanning in Bigeye.

Thought leadership

Live Keynote: Ensuring Trust Through Governed Agentic AI

A talk from The AI Summit New York on scaling AI safely without slowing innovation.

Thought leadership

Speed vs. Safety: The AI Dilemma Enterprise Leaders Are Facing

Enterprise AI leaders feel trapped between moving fast and staying safe.

Thought leadership

The House Of Data Series: Data Quality

Thought leadership

The House of Data Series: Data Architecture

Product

Introducing: Bigeye's AI Guardian

The AI Guardian acts as a data access gateway that evaluates every AI request against policies.

Thought leadership

The Data Quality Crisis Killing AI Projects (and Other Hard Truths.)

What BARC's new research uncovered about AI's biggest production challenges.

Product

Introducing: Sensitive Data Scanning

Today, we’re announcing Sensitive Data Scanning capabilities within Bigeye

Thought leadership

The House of Data Series: What Is The House Of Data?

A systems view of enterprise data.

Product

How We Turn Customer Needs into Product Features

Behind the scenes of working with customers to build their dream features.

Company

Life at Bigeye: Drew Stark, Head of Sales

Meet Drew, Head of Sales at Bigeye.

Product

How Does Bigeye Handle Your Sensitive Data? Our Field CTO Breaks It Down.

A technical breakdown of what data Bigeye stores, which features access raw data, and security configuration options.

Product

Inside Bigeye: How We Use AI to Solve Enterprise Data’s Biggest Problems

Machine learning, patent-pending tech, and automation built for enterprise data.

Thought leadership

Your GPAI Compliance Strategy Has a Vendor-Shaped Hole

How to audit your AI vendors (before they become regulatory nightmares,)

Company

Life at Bigeye: Tyler Jones, Senior Staff Software Engineer

Meet Tyler, Senior Staff Software Engineer at Bigeye.

Thought leadership

The CISO's Guide to Not Getting Blindsided by EU GPAI Rules: Part I, Foundations

If your understanding of EU AI Act compliance stops at "we use OpenAI Enterprise," you're about to have a problem.

Thought leadership

So You Want to Buy a Data Observability Tool– Now What?

You’re ready to buy a data observability tool, but are you aware of these considerations before you do?

Product

How NOV Built Data Confidence Across Eight Data Warehouses with Bigeye

Data observability success in the oil and gas industry.

Thought leadership

In Conversation with EY Park and Rahim Hajee: The 4 Pillars of Enterprise AI Success

A recap of the Toronto roadshow conversation with EY and Rahim.

Product

Monte Carlo vs Bigeye: An In-Depth Feature Comparison

Explore how Monte Carlo and Bigeye stack up across key features and use cases.

Company

Life at Bigeye: Alex Nouhan, Customer Success Engineer

Meet Alex, Bigeye's Customer Success Engineer.

Thought leadership

From Unaware to Operational: The 5 Stages of AI Trust Maturity

Explore the five stages of AI Trust maturity and what it takes to continue advancing.

Product

Bigeye Expands Data Quality Capabilities with Three New Features

Introducing: customizable data quality dimensions, join rules, and asset linking.

Thought leadership

How to Overcome AI Fear in Your Organization

Four strategies to overcome organizational AI anxiety.

Thought leadership

3 Enterprise Leaders on Building AI Agents That Actually Work

Enterprise leaders from Improzo, Frontdoor, and GlobalLogic share their experiences building AI agents.

Thought leadership

5 Hard-Won Lessons from the Frontlines of Enterprise AI Leadership

5 lessons from enterprise leaders who have been in the AI trenches.

Company

Life at Bigeye: Diane Worthington, People and Engagement Manager

Meet Diane, Bigeye's People and Engagement Manager.

Product

Enterprise Software Accessibility: Bigeye’s Approach to Inclusive Data Tool Design

Accessibility is deeply integrated into our development process. Here's how we approach it.

Thought leadership

AI Risk Management: The Gap Nobody Wants to Talk About

If you're not managing AI risk, you're not managing AI: you're chasing hype.

Company

Life at Bigeye: Riley Gercak, Event Marketing Manager

Meet Riley, Bigeye's Event Marketing Manager.

Thought leadership

Understanding Data Profiling: A Foundation for Better Business Intelligence

Learn how data profiling creates a solid foundation for reliable business intelligence and analytics.

Thought leadership

5 Questions to Pressure-Test Your AI Foundation

Five critical questions every data leader should ask to assess where your org is at with AI.

Thought leadership

AI Readiness Audit: The 5 Questions Every Data Leader Should Be Asking | Video Webinar

A practical framework for assessing whether your data is helping (or hurting) your AI strategy.

Thought leadership

Bridging the AI Hype Gap: Real-World Insights From Data Leaders On What It Takes To Succeed

Real talk from data leaders on closing the gap between AI hype and reality.

Product

Introducing Bigeye's AI Trust Platform

Bigeye is building the first AI Trust Platform for agent data usage.

Company

From My Seat: What Makes Bigeye a Great Place to Work

What our People & Engagement Manager sees behind the “Great Place to Work” badge.

Product

How Enterprise Data Teams Stay Ahead of Issues with Bigeye

A 20-minute walkthrough showing how Bigeye helps data teams succeed.

Company

Introducing Bigeye’s Matillion Connector

One of the world’s largest industrial tech companies needed Matillion lineage. So we built it.

Company

Bigeye is Great Place to Work-Certified™

Bigeye is now officially Great Place to Work-Certified™

Product

Introducing Bigeye’s Azure Data Factory Connector

Bigeye now integrates with Azure Data Factory.

Product

bigAI Is Now Generally Available

bigAI uses generative AI to do what most observability tools can’t.

Before You Build a Data Observability Tool, Read This

You know you need observability, but the next big question is: should you build your own?

Thought leadership

SLAs: Not Just for Software Engineers Anymore

SLAs have left the software engineering chat (and joined the data team.)

Thought leadership

Get AI Ready with Governance & Data Observability

A real look at how enterprise organizations use observability and governance to scale data trust.

Thought leadership

AI for Data Observability: Designing for Privacy, Access, and Risk

AI observability introduces new risks, here’s what you should know.

Thought leadership

AI is Reshaping CDO Leadership: What You Need to Know

This recap breaks down what CDOs need to know to stay ahead.

Product

Data Leaders Are Tired of Firefighting—Here’s How AI Can Help

We built bigAI to assist incident responders to rapidly understand data issues and fix them faster.

Company

Our 2025 Data Observability Trends and Predictions

Based on industry movements and customer conversations, here’s what we expect in the year ahead.

Thought leadership

Data Leaders’ 2025 Toolkit: Must-Have Observability Resources

With the complexity of enterprise data pipelines, ensuring trust in data is crucial. But where do you start?

Product

Achieving Data Transparency at Scale: Freedom Mortgage’s Success with Bigeye

We spoke with Eric Chesebro, executive vice president of data governance at Freedom Mortgage, to discuss how they’ve transformed their data governance strategy using Bigeye.

Company

Transforming Data Governance at Scale: Freedom Mortgage's Journey with Bigeye

In this video case study, see how Bigeye empowers Freedom Mortgage to achieve data transparency and efficiency at scale.

Thought leadership

Data Observability vs. Data Quality: Key Differences

Discover the critical roles of and key differences between data observability and data quality.

Engineering

How To Evaluate Data Observability Platforms (With Downloadable)

So you’re considering a data observability platform, but want to make sure you’re choosing the best one for your business. We’ve got some tips to help you run a thorough evaluation process.

Thought leadership

What is Data Quality Testing?

Discover what data quality testing is, why it matters, and techniques to ensure your data is accurate, consistent, and reliable.

Company

The Next Chapter for Bigeye: Realigning Our Leadership Team for the Future

Moving into the role of Chief Product Officer is a chance for me to focus entirely on what I’m most passionate about: solving our customer’s most critical problems with unmatched technology and design.

Product

Introducing Bigeye’s Looker Connector: Lineage-Enabled Observability for Looker Workflows

Tracking lineage in BI tools can often be a complex and manual process. The Looker Connector changes that.

Thought leadership

To Succeed In 2025, Data Engineers Need to Become More Lazy | The Jam Session feat. Kyle Kirwan

What does it mean for data engineers to "be lazy"? It’s about working smarter, not harder. Industry leaders—including Bigeye CPO Kyle Kirwan—discuss live.

Product

Introducing Bigeye’s New Lineage-Enabled Workflows: Helping You Resolve Data Incidents Faster

Powered by Bigeye’s lineage graph, these workflows use downstream impact to prioritize issues, helping data engineering teams focus on what matters most.

Thought leadership

Only 28% of Organizations Trust Their Data: How Data Observability is Transforming Enterprise Reliability

Only 28% of organizations trust their data—here’s why two-thirds of enterprises are turning to automated observability to change that.

Thought leadership

The Future of Data Observability: Trends and Predictions for 2025 | Webinar

Thought leadership

What is Data Reliability?

Explore the essentials of data reliability and why it matters to enterprise organizations.

Thought leadership

A Quick Guide to Data Observability Tools: Finding the Best Fit for Reliable Data

Looking to improve data quality and reliability? This quick guide explores top data observability tools, from specialized solutions to built-in features, helping you find the best fit for monitoring and optimizing your data pipelines. Discover the tools that can elevate your data observability strategy.

Thought leadership

How to Measure the ROI of Your Data Observability Platform: Five Key Metrics

If you’ve made the investment in data observability, the next challenge is figuring out how to measure whether it’s actually working.

Thought leadership

The Four Pillars of Data Observability

Discover the core pillars of data observability and how they provide the essential insights needed to monitor, manage, and improve data health.