Data Lake with Informatica & Snowflake, Sovereign AI Research and more

Reimagine data integration for AI-powered insights

Most AI programs stall because the data is hard to find, hard to trust, and slow to move. This webinar uses Paycor’s journey to show a simple path to AI-ready data with Informatica IDMC and Snowflake.

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Why this matters

• Teams waste time cleaning and reworking data instead of analyzing it

• Slow reporting cycles block decisions and delay AI use cases

• Without traceability, it is hard to scale safely

What you will learn

• The before and after at Paycor: reporting cycles cut from months to minutes and data wrangling reduced by 90 percent using Informatica with Snowflake

• A practical flow: ingest, clean, validate, publish, and monitor

• Simple ways to add quality checks and track data changes so analytics and GenAI stay reliable

• How to organize people and process so pipelines stay fast without adding debt

Who should attend

Data leaders, platform teams, analytics engineers, and practitioners who want a clear starting point for AI-ready data.

Speakers

• David Samuel, Sr. Manager of Data Engineering, Paycor

• Venkat Suru, Field CTO of Data Platform Architecture and Data Apps, Snowflake

• Amol Dongre, Sr. Director of Product Management and Data Integration, Informatica

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Digital sovereignty is not a future issue. It is a daily decision for any team building with data and AI. I went through EDB’s new “Sovereignty Matters” report and it is a clear guide for leaders who want control without slowing teams.

What stood out to me:

- Why sovereignty matters now: customer trust, compliance, uptime, and cost control.
- Data stays where it should: how to think about region choice, residency, and lawful access.
- Control with choice: the role of open technologies, portability, and avoiding hard lock-in.
- Cloud, on-prem, and hybrid: simple frameworks to pick what runs where and why.
- AI angle: placing models and data close to each other, monitoring usage, and proving you are in control.
- Practical steps: map data flows, define ownership, log access, plan an exit path, and test it.

Who should read this:
• Product and platform teams adding AI features
• Security, compliance, and privacy leaders in regulated industries
• Founders and buyers who want leverage in vendor negotiations

How to use it this quarter:
• List your sensitive datasets and the countries they touch
• Decide where the control plane and data plane live
• Write a simple portability plan before you sign the next contract
• Turn on audit logs, retention, and regular reviews
• Align legal, security, and engineering on a single page of guardrails

I am also sharing a short carousel with my notes and takeaways for a quick skim.

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Best,

Ravit Jain

Founder & Host of The Ravit Show