Data Platform Reliability & Architecture Assessment
Identify reliability, performance, scalability, and operational risks in your data platform before they become expensive engineering problems.
A structured technical assessment for CTOs and engineering leaders at growing SaaS and technology companies that need clearer visibility into their data platform's current challenges and practical next steps.
The problem
Your data platform can become a bottleneck long before it completely breaks.
As data volumes, users, products, and engineering teams grow, data platforms often accumulate architectural and operational complexity.
Problems may appear as unreliable pipelines, slow workloads, increasing infrastructure costs, difficult troubleshooting, fragile dependencies, or systems that are becoming harder to scale.
The challenge is often not identifying that something is wrong. It is understanding where the problem originates and what should be addressed first.
Who this is for
Built for growing SaaS and technology companies
This assessment is designed for engineering organizations where the data platform has become strategically important and the technical team needs an independent view of its architecture, reliability, and scalability.
Growing data volumes
Your platform is processing significantly more data than it did previously.
Pipeline reliability issues
Failures, delays, retries, or operational incidents are becoming difficult to manage.
Scaling concerns
You are unsure whether the current architecture will support the next stage of growth.
Increasing complexity
More systems, tools, dependencies, and pipelines are making the platform harder to understand.
Performance problems
Queries, processing jobs, or downstream workloads are taking longer than expected.
Architecture uncertainty
Your team needs an independent technical assessment before making significant platform decisions.
What we review
A technical review across the areas that influence platform health
Architecture
- Overall data platform architecture
- System boundaries and dependencies
- Data flow and processing patterns
- Technology choices and architectural fit
Reliability
- Pipeline failure patterns
- Retry and recovery mechanisms
- Monitoring and alerting
- Operational dependencies
Performance
- Processing bottlenecks
- Query and workload patterns
- Data movement and processing efficiency
- Potential areas of technical contention
Scalability
- Growth-related architectural risks
- Capacity considerations
- Scaling patterns
- Potential future bottlenecks
Data engineering
- Pipeline design
- Data quality considerations
- Transformation architecture
- Orchestration patterns
Operations
- Observability
- Incident response considerations
- Deployment and operational practices
- Maintainability
What you receive
A technical assessment your engineering team can act on
The objective is not to produce a generic architecture report. The assessment should help your team understand the current situation and determine what deserves attention first.
Executive-level summary of key findings
Architecture and reliability observations
Performance and scalability risk areas
Operational and maintainability observations
Prioritized recommendations
Suggested next steps
Illustrative report structure
Example of how findings can be structured
The final report is tailored to your platform. A typical assessment may include sections such as:
01
Executive Summary
Major observations, risks, and areas requiring attention.
02
Technical Findings
Architecture, reliability, performance, scalability, and operational findings.
03
Recommended Actions
Practical recommendations and potential priorities for the engineering team.
Investment
Starting at $1,500
The starting price covers a defined technical assessment scope. Final pricing depends on platform complexity, data volume, number of systems, and assessment depth.
The assessment can include
- ✓Initial technical discovery
- ✓Architecture review
- ✓Reliability review
- ✓Performance considerations
- ✓Scalability assessment
- ✓Operational review
- ✓Findings report
- ✓Recommended next steps
Process
From initial conversation to actionable findings
Request
Tell us about your company, platform, and current challenge.
Discovery
We clarify the architecture, systems, workloads, and assessment objectives.
Assessment
We review the agreed technical areas and identify relevant findings.
Recommendations
You receive a structured summary of findings and practical next steps.
Technical experience
Built from hands-on data engineering experience
Big Data Technologies brings more than 12 years of experience across database and data engineering environments, with a focus on data platforms, architecture, pipelines, cloud data infrastructure, and engineering challenges.
Request an assessment
Request a Data Platform Assessment
Share a few details about your company and data platform. We will review the information and follow up to understand whether the assessment is a good fit.