How to Solve the Biggest Challenge for Data Engineers: Snowflake Warehouse Optimization and Cost Reduction Without the Hassle

Are you a Data Engineer or Snowflake Admin tired of battling warehouse optimization?

You’re not alone.

 Over the past five months, we’ve talked to over 70 Snowflake users – Data Engineers, Data Architects, Heads of Data – and they all had the same frustration:

“How do I make sure my warehouse is the right one?”

Discover how Angel Studios reduced their Snowflake costs by 60% in just 54 minutes – without any query changes.

Click here to download the full case study PDF

The Challenge: Wasting Time on Infrastructure Instead of Data

Data professionals want to work with data, not deal with infrastructure headaches.

But too many of us are getting stuck managing warehouse settings, wasting valuable time that should be spent on insights and strategy.

Common Frustrations:

• Inefficient Warehouse Utilization: Constantly second-guessing whether your warehouse is over-provisioned or underused.

• Resource Optimization Struggles: Balancing cost and performance feels like a never-ending battle.

• Infrastructure Burden: Instead of focusing on data analysis, you’re spending time configuring warehouse settings.

A Personal Journey: From Frustration to Solution

When I first started using Snowflake five years ago, I couldn’t get this question out of my head:

“Is my warehouse fully optimized?”

That question haunted me. I was wasting too much time trying to figure out if I was using the right settings instead of actually analyzing the data I cared about. I knew there had to be a better way.

The Solution: Applying DevOps Methodologies to Snowflake

The game changer was integrating DevOps methodologies into Snowflake. 

We stopped worrying about infrastructure and let automation do the heavy lifting. 

This allows data teams to focus on what really matters: the data.

Benefits of This Approach:

• Automated Warehouse Optimization: No more guessing about warehouse sizes – let automation do the work.

• Cost Efficiency: Cut down on unnecessary spending by optimizing your resources.

• Enhanced Focus on Data: Get back to analyzing data instead of babysitting infrastructure.

• Scalability: Handle changing workloads with ease, no manual tweaks required.

Case Study: How Angel Studios Reduced Their Snowflake Bill by 60%

We tested our Plug&Play solution with Angel Studios, and the results were amazing:

Key Outcomes:

• 60% Reduction in Snowflake Costs: Major savings, less spend.

• Time Efficiency: All done in just 54 minutes.

• Zero Query Changes: Improved performance without touching a single query.

• Refocused Efforts: Freed up the team to focus on data, not infrastructure.

Download the full case study PDF to see the full story and learn exactly how we made it possible.

Why This Matters

When data teams can focus on the data itself, great things happen. Shifting away from infrastructure problems means you can unlock more insights, make better decisions, and ultimately gain a competitive edge.

Imagine If You Could:

• Spend more time analyzing data and less on warehouse configurations.

• Reduce costs without losing out on performance.

• Effortlessly scale your data operations as your needs grow.

Take the Next Step

Don’t let infrastructure headaches hold your data team back. 

Take control of your Snowflake warehouse, and get back to what you do best – working with data.

Ready to optimize your Snowflake warehouse without the headache?

• Download the Angel Studios Case Study PDF to learn more.

• Contact Us to see how we can help you achieve the same results.

By using DevOps methodologies with Snowflake, we’re redefining how data teams work.

Let’s make data the focus again.