Building a modern Data & AI stack with Snowflake: the KPC masterclass

From how the Data Warehouse has evolved to integrating generative AI, see why this platform has become an essential foundation for companies.

In this new episode of Robin Conquet's DataGen podcast,  Mickael Kuentz, Data & AI Director at KPC, sets out the keys to building a high-performing Data and AI architecture with Snowflake.

Snowflake: freeing data so you can make more of it

Snowflake came out of a simple promise: separate compute from storage to lift the limits of traditional platforms. The result: extremely fast processing, even on very large volumes. As Mickael Kuentz puts it, “ Snowflake freed the data ” by making it possible to query billions of rows smoothly.

From data warehouse to complete platform

Originally designed as a Data Warehouse, Snowflake quickly widened its reach. Today the platform covers every workload in the modern data stack: ingestion, transformation, visualization, machine learning, generative AI and even application development.

With tools like Streamlit and Snowpark Container Services, Snowflake now lets you build applications and bring AI models right into the data.

The advantages and the limits worth knowing

Main advantages:

• Simplicity and speed: lighter implementation and administration.

• Scalability: suits startups and large groups alike.

• Functional coverage: a complete range of use cases.

Points to watch: The main risk is still vendor lock-in, even though Snowflake keeps investing in interoperability (Apache Iceberg, Microsoft partnerships).

Generative AI: the underlying trend

Snowflake has made generative AI a major strategic focus. AI now supports governance (e.g. Copilot Horizon) and speeds up putting business use cases in place. In parallel, Snowflake is becoming a secure foundation for running GenAI models (OpenAI, Mistral, Anthropic, Meta).

Advice for a successful Snowflake project

• Check the organizational prerequisites: maturity, a clear use case, internal sponsorship.

• Build a stack that fits : choose the right third-party tools for your needs.

• Open data up: make the platform accessible to business profiles.

• Get ahead of AI : build AI into your data strategy now.

Why listen to this podcast?

This podcast is a genuine masterclass for data leaders, CTOs and IT decision-makers.

Mickael Kuentz shares not only his technical expertise but also practical and strategic advice based on several years of project experience.

You get to see how Snowflake combines performance, simplicity and innovation, while staying alert to questions of governance and sovereignty.

If you want to understand concretely how to build a high-performing Data & AI stack, this episode will give you valuable keys and inspiring lessons from the field.