Agentic EDA with AI Foundry: Automating Exploratory Analysis
6 min read12 hours ago
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We’re all familiar with the power of large language models when it comes to processing unstructured data. What’s far less intuitive — and often confusing (for some) — is how these same models can be used to analyze structured data. In this article, I explore one of the ways agentic systems can be used to work with structured data.
As a data scientist, I’ve always been drawn to the sheer potential of data. There’s something almost magical about taking raw numbers, messy tables, and unstructured information and turning them into insights that actually influence decisions and spark innovation. But for all its excitement, there’s one part of the machine learning workflows that consistently slow…
Agentic EDA with AI Foundry: Automating Exploratory Analysis
6 min read12 hours ago
–
We’re all familiar with the power of large language models when it comes to processing unstructured data. What’s far less intuitive — and often confusing (for some) — is how these same models can be used to analyze structured data. In this article, I explore one of the ways agentic systems can be used to work with structured data.
As a data scientist, I’ve always been drawn to the sheer potential of data. There’s something almost magical about taking raw numbers, messy tables, and unstructured information and turning them into insights that actually influence decisions and spark innovation. But for all its excitement, there’s one part of the machine learning workflows that consistently slows things down: Exploratory Data Analysis (EDA).
And if you’ve ever worked on a real-world data project, you know exactly what I’m talking about.
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The Challenge: When EDA Becomes a Roadblock
EDA is where we get to know the data — really know it to understand how it can be used to build models . We summarize key variables, visualize distributions, check for outliers, find patterns, and explore relationships. It’s the detective work that lets us build models that actually perform well, instead of relying on guesswork or assumptions.