Entering the Era of Data + AI Observability

In the age of AI, data is taking on a whole new life. But, how are organizations managing it? And more importantly, how are they managing its quality??

A rising tide raises all boats—but AI isn’t a tide, it’s a tidal wave. Play your first-party data cards right and you can ride that wave all the way to the bank. Drop the ball…and you’ll probably be looking for a new ship.

Nautical analogies notwithstanding, data quality matters. And in this edition, we’ll explore how data + AI teams are managing data quality across the AI development life cycle—and how you can get started with data + AI observability.?

• ?? Why we’re entering the era of data + AI observability?
• ?? This month’s hot, medium, and mild takes on AI, data engineering, and more
• ?? Info on upcoming events, like our Serving Data dinner series
• ??And our meme of the month (of course)

What’s new??

What we’re writing about:

• 2026 Will Be the Year of Data + AI Observability. Data and AI are no longer two separate technologies; they’re two halves of a single system. Monte Carlo CEO Barr Moses shares why it's time to start treating them that way.?
• Monte Carlo and Databricks Partner to Deliver Data + AI Observability. We’re excited to also announce our expanding our partnership with Databricks to extend data + AI observability into the AI pipelines built on Databricks' Data Intelligence Platform.
• Monte Carlo & Snowflake Partner to Deliver Observability for Unstructured Data. This expanded partnership will make it easier for data organizations to build, train, and deploy reliable agents with Cortex AI—and drive more AI value along the way.

What we’re talking about:

• AI-Ready Data: Forging the Path to Scalable & Reliable AI. If AI is everywhere, how do you stand out? Monte Carlo CTO Lior Gavish joined Data Science Dojo to share why first-party data is the greatest moat for AI—and how to get your data AI-ready.?
• AI Without Mistakes: How Good Data Makes It Happen. Looking for your competitive edge in the AI arms race? Barr Moses joined the Eye on AI podcast to share how data teams can create competitive advantage with AI in 2025.
• I Like to Think of Myself as a Data Monetization Expert. CDO Magazine shared an interesting conversation with Lori Sherer, Partner at Bain & Company, where she dove into the pivotal moments that shaped her journey and her experience bridging the gap between data science and business value.

What’s hot? ???

We share one hot take, one medium take, and one mild take on what’s happening in the data space. Can you handle the heat?

• Hot: Working as a data engineer sucks… Or does it? BitsOnFire analyzed hundreds of posts from r/dataengineering, and it turns out it’s not all sunshine and rainbows in the data world. But is it really all blizzards and heatwaves? Check out the report to find out.
• Medium: You’re data team isn’t as close to your business as you think. Barr Moses recently shared what she believes every CDO needs to know to be truly AI-ready. At the top of the list—attention to semantics, governance, first-party data … and a desperate need to get closer to your business users.?
• Mild: Apache Iceberg is the new Hadoop? Ananth Packkildurai of Data Engineering Weekly shared his latest conversation offering a critical look at Iceberg's potential—and the hurdles organizations face when adopting it.

Let’s meet up!

Every season is data events season – and that’s just the way we like it. Catch us here next:

• Serving Data: Toronto and Serving Data San Francisco: We’re heading to Toronto on March 20 and San Francisco on April 2! Join us at one of these events to enjoy dinner, drinks, and plenty of AI discussion with your local data leaders.
• Optimized AI Conference: Heading to the Optimized AI Conference in Atlanta? Don’t miss Monte Carlo Field CTO Shane Murray speaking on the hidden hurdles of GenAI success on April 14!
• Gartner Data & AI Summit in London: We’ll be at Gartner Data + Analytics Summit on May 12-15! Will we see you there?

What we’re reading:

Here’s a few articles from across the industry that piqued our interest this month.?

• Unlocking the Potential of AI Agents: From Pilots to Production Success. Databricks recently published an article outlining the importance of data quality for trusted and scalable AI agents.?
• AI just got better… again? Ethan Mollick of One Useful Thing shared why the new generation of AIs, Claude 3.7 and Grok 3, might tell us something important about where AI is going.
• The Real Impact of Bad Data on AI Models. How bad is “bad” when it comes to data feeding your AI and ML models? And how can you know when data quality has deteriorated enough to actually impact your business? AI researchers Andrew Koller and Chris Bosley aim to find out.

Just for Fun

Bad data is coming for your AI models…

Until next time! Stay reliable!