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Most conversations about automating data workflows center on the engineering stack—but that’s only part of the story. The real payoff comes downstream, where data scientists, analysts, and business leaders need fast, reliable access to data to make informed decisions. In this session, the Matillion team will demonstrate how an agentic system like Maia shifts repetitive data tasks into autonomous execution, freeing up teams to focus on high-impact analysis and modeling.

We’ll walk through how this shift reduces backlog, accelerates time-to-insight, and increases trust in the data that drives both machine learning pipelines and executive dashboards. Through real-world examples, attendees will see how agentic workflows empower the entire data organization—not just engineering.

Key Takeaways:

1️⃣ Workload Lift for Analysts & Scientists: How automation reduces manual prep and speeds up modeling cycles

2️⃣ From Backlog to Business Value: How agentic orchestration gets more data into production, faster

3️⃣ Organizational Trust in Data: Why agentic systems improve confidence in the data used for decision-making

4️⃣ Cross-Functional Impact: How these changes improve collaboration between data engineering, analytics, and leadership teams

PANELISTS TO BE ANNOUNCED SOON

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Sponsors

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Amazon Web Services (AWS)
Presenting Sponsor
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TIBCO
Exhibiting Sponsor
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UVA School of Data Science
University Sponsor

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