Data & AI Architecture Review
Strategic audit of your platform against modern patterns (Lakehouse, Mesh, Fabric) to support high-throughput AI workloads.
What You Get
A comprehensive technical assessment of your data platform architecture, evaluating scalability, performance, cost-efficiency, and alignment with modern architectural patterns like Data Lakehouse, Data Mesh, and Microsoft Fabric.
Perfect for organizations planning platform modernization or experiencing performance bottlenecks in their current data infrastructure.
Key Metrics
Review Areas
Data Storage Layer
Storage architecture, partitioning strategy, and data lake/warehouse design
Processing Engine
Batch and streaming pipelines, compute optimization, and orchestration
Cloud Architecture
Multi-cloud strategy, service selection, and cost optimization
Integration Patterns
API design, event-driven architecture, and data movement patterns
Performance & Scale
Throughput analysis, latency optimization, and scalability assessment
AI/ML Infrastructure
Model training, deployment, and MLOps capabilities
Deliverables
Current State Assessment
Detailed documentation of existing architecture, technology stack, and data flows.
Gap Analysis
Comparison against modern reference architectures (Lakehouse, Mesh, Fabric) with identified gaps.
Target Architecture Blueprint
Future-state architecture design with technology recommendations and migration paths.
Performance Optimization Plan
Specific recommendations for improving throughput, reducing latency, and optimizing costs.
Migration Roadmap
Phased approach to transitioning from current to target state with risk mitigation strategies.
Modern Data Architecture
Modern data architecture enabling both analytics and AI workloads on unified infrastructure
Ready to Modernize Your Architecture?
Get expert guidance on building a scalable, future-proof data platform.
Schedule a Consultation