- Travel & Hospitality
Optimizing data pipeline efficiency to reduce cloud costs for an amusement park
Overview
Optimizing Snowflake costs for smarter data spend
Many organizations invest in modern cloud data platforms like Snowflake to support data-driven decision-making and innovation. However, without proper cost management, these investments can grow disproportionately to their value. A seaside amusement park client approached us with a significant challenge: their Snowflake costs were spiraling beyond expectations despite what they believed should be a relatively modest data workload. They needed clarity on cost drivers and actionable recommendations to align spending with business outcomes.
Our Solution
Executing in-depth cost analysis and actionable strategies
We performed a comprehensive analysis of the organization’s Snowflake environment, focusing on spend trends, workload efficiency, and resource allocation. The engagement included:
- Macro-level spend assessment: Identified trends and major cost contributors within the organization’s Snowflake environment.
- Detailed workload profiling: Drilled into high-cost applications and workloads, uncovering inefficiencies driving excess expenditure.
- Actionable cost-saving recommendations: Delivered a set of tailored strategies to reduce costs while maintaining operational effectiveness.
Two primary inefficiencies emerged during our analysis:
- High-cost applications with minimal value: One application alone consumed over 30% of total Snowflake costs, but didn’t represent significant business value.
- Overly frequent processing schedules: Frequent data loads without real-time needs can inflate costs. Aligning processing frequency with business value reduces waste and maintains efficiency.
To sustain cost efficiency, we suggested leveraging Snowflake’s built-in tools, such as resource monitors, auto-suspend settings, and budgets with usage alerts, ensuring proactive cost management aligned with evolving business needs.
Results
50% cost reduction and a foundation for long-term efficiency
Our engagement delivered immediate and impactful results:
- 50% reduction in Snowflake spend: Shutting down the underperforming application and adjusting the data pipeline frequency achieved nearly half of the total savings.
- Improved cost visibility and control: Introducing workload-specific warehouses allowed precise tracking of resource usage, enabling better budget alignment.
- Sustainable cost management: Implementing Snowflake’s monitoring tools created a feedback loop for ongoing optimization.
These changes not only aligned Snowflake costs with the organization’s data workloads but also created a foundation for sustainable growth. By reducing unnecessary expenses and enhancing efficiency, the organization could reinvest savings into high-value data initiatives, driving innovation and competitive advantage.
Are you looking to optimize your cloud data spend and unlock the full potential of your Snowflake investment? Contact us to learn how we can help you achieve impactful results like these.
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