Structured for Success: A Real-World Perspective on Snowflake from nvisia

As data architecture continues to evolve, so does our toolkit. At nvisia, we’ve been actively exploring modern platforms that balance flexibility, cost-efficiency, and scale.

One of those platforms is Snowflake—and thanks to Taylor Sullivan, Delivery Lead in our Milwaukee region, our team recently got a practical, candid walkthrough of what Snowflake is, how it works, and what to expect when preparing for certification.

This post recaps Taylor’s lightning talk to help fellow technical leaders and data engineers understand whether Snowflake might be a good fit—and where it stands out in today’s crowded cloud ecosystem.

What Is Snowflake (Really)?

Taylor broke it down clearly: Snowflake is a cloud-native, managed data warehouse that offers a “lakehouse” architecture—combining the freedom of data lakes with the order of structured warehouses. It’s designed to:

• Run in AWS, Azure, or GCP
• Support structured and semi-structured data
• Scale horizontally with on-demand compute
• Separate compute from storage (for better efficiency and cost control)
• Offer a familiar SQL-based interface with a few bonus powers (like COPY INTO, time travel, and more)

It’s also multilingual, meaning you can access Snowflake through Python, JavaScript, SQL, APIs, or native packages depending on your tech stack.

Why Choose Snowflake?

Taylor’s perspective centered on real-world decision-making. Here are some highlights from his insights:

• OpEx Advantage: You pay only for what you use. When you log off, Snowflake scales down—saving money in a way traditional on-prem systems can’t match.
• Ease of Use: If you know SQL, you can use Snowflake. The interface is intuitive, and the web-based "Snowsight" makes it simple to get started.
• Scalability: Snowflake automatically spins up additional compute resources as more users or queries hit the system—without impacting performance.
• Columnar Storage & Micro-Partitioning: Optimized storage design enables faster queries and lower costs, especially for relational data models.
• Decoupled Compute & Storage: This architecture makes it easier to scale compute independently of how much data you store.

Databricks vs. Snowflake?

Taylor didn’t shy away from the big question: how does Snowflake compare to Databricks?

• Databricks excels at machine learning, unstructured data, and notebook-based workflows (Python-heavy).
• Snowflake shines in BI, structured analytics, and enterprise-scale SQL workloads.

As Taylor emphasized, the right choice depends on your goals. Snowflake may be ideal for teams focused on BI, reporting, and scalable data warehousing, while Databricks might win in AI R&D or custom model development.

What’s on the Certification Test?

In true nvisia fashion, Taylor offered pragmatic advice for those pursuing Snowflake certification:

• Expect questions on data transformation, security, and AI features.
• Brush up on SQL layers (DML, DDL, DCL), views vs. stored procedures, and partitioning logic.
• Snowflake’s AI tools are now increasingly emphasized in exams—be sure your course materials are current.
• Avoid outdated prep materials (some courses still reference deprecated features like Snowpark Classic).
• Consider in-person testing if you want to avoid strict remote proctoring rules.

Taylor also shared a library of notes and resources via internal Confluence and recommended a specific Udemy course for hands-on prep.

Ready to Explore Snowflake?

This session is part of our broader initiative at nvisia to upskill teams and assess data technologies from a consulting perspective—not just certification. We work alongside clients to:

• Select the right cloud data architecture
• Build scalable pipelines and analytics environments
• Train internal teams on platforms like Snowflake or Databricks
• Evaluate AI capabilities in real-world contexts

If your team is deciding between platforms or looking to get more from your data, reach out. We’d love to share what we’ve learned and help guide your path.

👉 Explore our Data & AI Services

👉 Or connect with us directly for a consultation

Originally published on nvisionaries on LinkedIn.