Data Platform Audit
Teams struggling with pipeline instability or high costs need clarity on their data stack. We assess reliability, scalability, and cost, identify risks and bottlenecks, and provide an optimization roadmap.
Why Data Platform Audits Matter
Data platforms can become unreliable, expensive, or unscalable over time. Pipeline instability blocks delivery, rising costs eat budgets, and bottlenecks prevent growth. A comprehensive audit identifies issues and provides a clear optimization roadmap.
This service is perfect for teams struggling with pipeline instability or high costs. We assess your data stack, identify risks and bottlenecks, and provide an optimization roadmap to improve reliability, scalability, and cost efficiency.
Key Facts & Examples
Data Platform Costs
Organizations spend an average of $2.3 million annually on data platforms, with 30–40% of costs wasted on inefficient architectures, unused resources, and failed pipelines. Platform instability causes 15–25% of data projects to fail or exceed budget.
Common Data Platform Issues
- Pipeline Failures: Unreliable data pipelines fail 10–20% of the time, causing reporting delays, data gaps, and operational disruptions
- Cost Overruns: Data platform costs grow 25–40% annually without optimization, with underutilized compute and storage being primary drivers
- Performance Bottlenecks: Slow queries and inefficient data models cause dashboards to take 30–120 seconds to load, reducing adoption by 50–70%
- Scalability Gaps: Platforms that can't scale cause 20–30% of data initiatives to fail when data volumes grow beyond initial capacity
Real-World Example
A fintech company's data platform costs grew from $45K to $180K monthly over 18 months, with pipelines failing 15% of the time. A platform audit identified $95K in wasted compute from inefficient Spark jobs, $35K in unused storage, and pipeline reliability issues from missing error handling. Implementing recommendations reduced costs to $85K monthly and improved pipeline reliability to 99.5%.
How It Works
A structured process tailored to this engagement
Stack Assessment
Review data infrastructure, tools, and pipeline architecture
Risk Analysis
Identify reliability risks, bottlenecks, and scalability constraints
Cost Review
Analyze platform costs and identify optimization opportunities
Optimization Roadmap
Provide prioritized roadmap with recommendations and impact estimates
What You'll Receive
Clear, actionable deliverables
Data platform stack assessment
Reliability & scalability analysis
Cost analysis & optimization opportunities
Risk & bottleneck identification
Performance optimization recommendations
Optimization roadmap & implementation plan
Good Fit If
- Access to repos and tooling
- Read-only permissions preferred
- Remote sessions only
Outside Scope
- Implementation work
Ready to Get Started?
Let's discuss how Data Platform Audit can help your team achieve your goals.