Hi Data & AI Pros,

Tired of fragile data pipelines that only connect parts of your stack and cost an arm and a leg? Unsure when Openflow will be ready for enterprise-grade pipelines?

Join us for a live demo on June 26, 1pm ET, to see how CData’s Snowflake Ingest Toolkit simplifies data movement with CDC and intelligent replication, that rapidly connects Snowflake to any data source.

What you’ll learn:

• How to build no-code data ingestion with CDC into Snowflake from 270+ sources (APIs, databases, SaaS)

• Leverage native COPY INTO support for performant data loading and staging with S3, Azure, etc.

• Cut delivery lag (like Empower Services did— by 12 hours per report!)

• Make your costs predictable with Volume-independent pricing

Plus, get a sneak peek at CData’s Cortex AI Integration toolkit to supercharge your AI workloads in Snowflake.

See it in action with CData’s Cameron Leblanc.

I also got a chance to interview Amit Sharma, CEO of CData Software, at the Data + AI Summit on The Ravit Show, and we dove into a critical but often overlooked topic: data connectivity for AI agents. With the rise of agentic AI, the old ways of integrating data just don’t cut it. Amit broke down why real-time, context-aware access is now a must — and how CData is helping lead that shift.

Check out the complete interview below —

Kafka is powerful

— but no one talks about how messy it gets at scale. I recently came across this amazing ebook and it resonates so well. Learn more here

We hear it in conversations with engineers, platform leads, and data architects:
🔹 “Why is this Kafka pipeline so brittle?”
🔹 “We have no idea who owns what.”
🔹 “Data quality is killing downstream teams.”

A recent read that really stood out for me breaks down 5 unexpected challenges organizations face when scaling Kafka — and why it’s not just a tech problem, but a people and process problem too.

Here are the 5 silent blockers that show up again and again:

- Low-quality data = low trust and poor AI/analytics outcomes
- Overly manual workflows that bottleneck innovation
- Silos between ops and analytics teams, causing friction
- Zombie infrastructure quietly draining cloud budgets
- Fragmented legacy + cloud tech making integration fragile

Each of these issues is explained with real-world stories and solutions from teams that faced them — including postal services, retailers, and logistics companies.

If Kafka is part of your architecture, I highly recommend you check this out. It’s practical, relatable, and doesn’t sugarcoat the hard parts.

📘 Grab the full ebook here

If you're working with Kafka and want to get ahead of these scaling issues, this one’s worth a read. Let me know what stood out for you from it.

Go beyond prompt-writing.

Apply AI at work with step-by-step guidance from Columbia Business School faculty.

Learn to:

• Predict outcomes

• Streamline tasks

• Optimize decisions

No technical background required.

Enroll today in the AI for Business & Finance Certificate Program from Columbia Business School Exec and Wall Street Prep.

P.S. Save $300 with code SAVE300

Save Your Seat

🔍 Stay Ahead in AI & Data! Join 137K+ Data & AI professionals who stay updated with the latest trends, insights, and innovations.

📢 Want to sponsor or support this newsletter? Reach out and let's collaborate! 🚀v

Best,

Ravit Jain

Founder & Host of The Ravit Show