Data Transformation Strategies with Snowflake: Choosing the Right Approach for Every Pipeline

This is Part 2 of a 2-part series. Before you transform data, you need to get it in. If you haven't already, register for 7 October: AI-Ready Data Ingestion with Snowflake, using the same decision-framework format, focused on ingestion patterns.

Views, Dynamic Tables, Streams & Tasks, Snowpark, AI functions, DBT Projects, Materialized Views — once your data is in Snowflake, there are many ways to transform it. Knowing which to use, and when, is what separates simple, maintainable pipelines from over-engineered ones. 

In this session we cut through the options with a simple, repeatable decision framework that maps any transformation requirement to the right Snowflake capability — starting from a declarative-first default and stepping outside it only when the requirement truly demands it.

What you'll learn:
 

• A repeatable framework for matching a transformation requirement to the right Snowflake capability

• Declarative vs imperative: when Dynamic Tables are the right call, and when you still need Streams & Tasks

• SQL vs Python/Scala/Java: when to reach for Snowpark — and how to bring existing Spark workloads onto Snowflake

• How to match freshness requirements to the right refresh model without over-engineering

• How to turn unstructured data into structured output with AI, declaratively
  

What we'll cover:
 

• The transformation landscape: declarative vs imperative, SQL vs code

• The SQL and ELT baseline

• Declarative pipelines with Dynamic Tables

• Imperative pipelines with Custom Incremental Dynamic Tables

• Code-based transformation with Snowpark and Snowpark Connect for Apache Spark

• Transforming unstructured data with Cortex AI

• Operationalizing pipelines as code using DCM?

• A capability selector you can take back to your team
  

Who should attend: Enterprise and data architects, data-engineering team leads, and data engineers who want a clear mental model for transformation decisions — no click-by-click tutorials, just the when and what.