Data Architecture

Build the foundation that scales. Modern data platforms designed for lakehouse architectures, real-time analytics, and AI readiness.

Problem

Legacy Data Platforms Limiting Growth

Expensive data warehouses that can't handle new workloads. Fragmented storage across data lakes and databases. Architectures designed for batch reporting now facing real-time AI demands.

• Warehouse costs growing faster than business value
• Inability to support real-time analytics and ML
• Data duplication across lakes, warehouses, and databases
• Vendor lock-in limiting technology choices

Modernize Data Architecture

Approach

Cloud-Native Data Platforms

We design scalable data architectures using lakehouse patterns, separating storage from compute, and enabling multiple processing engines on unified data.

Lakehouse Architecture

Unified platform combining data lake flexibility with warehouse performance for all workloads.

Multi-Engine Processing

SQL, Spark, and AI frameworks accessing the same data without duplication or movement.

Data Mesh Principles

Domain-oriented architecture with federated governance and self-service data products.

Cost Optimization

Storage tiering, compute autoscaling, and workload optimization reducing data platform costs.

Business Impact

What You Actually Get

A data platform that scales with your business and supports AI.

Lakehouse

Unified Platform

Data lake flexibility with warehouse performance. All workloads on one platform.

Flexible

Multi-Engine Support

SQL, Spark, and AI frameworks accessing the same data without duplication.

Optimized

Cost Efficiency

Storage tiering and compute autoscaling. Pay for what you use, not what you provision.

Why Cloud2

Modern Data Architecture Expertise

Cloud-native data platforms designed for scale, AI, and cost efficiency.

Lakehouse Patterns

Unified storage with multiple processing engines. Best of data lakes and data warehouses.

Multi-Cloud

Databricks, Snowflake, AWS native, Azure Synapse, BigQuery. We design for your requirements.

AI-Ready

Architecture designed for AI workloads from the start. Vector storage, MCP compatibility included.

Domain-Oriented

Data mesh principles with federated governance. Teams own their data products.

Success Stories

Proven in Production

Real customers, real results. No hypotheticals.

Engineering & Consulting

COWI

AWS cloud infrastructure for GDPR-compliant image processing at scale

30 million

HD panoramic images processed

Manufacturing

TWP Group (twoAI)

Managed AI data solution for field service optimization

Significant

Time savings in field service operations

View all references

FAQ

Common Questions

What's a lakehouse architecture?

A unified platform combining data lake flexibility (any format, any scale) with data warehouse performance (fast queries, ACID transactions). Best of both worlds.

Which platforms do you recommend?

Depends on your requirements. Databricks, Snowflake, AWS native services, Azure Synapse, or BigQuery. We’re platform-neutral.

How do you handle legacy data warehouses?

Incremental migration. We move workloads to modern platforms while keeping existing systems running. No big-bang migration.

What about data mesh?

Domain-oriented architecture with federated governance and self-service data products. We implement the principles that fit your organization.

How do you optimize costs?

Storage tiering, compute autoscaling, workload scheduling, and reserved capacity. Data platform costs stay predictable.

Field Notes

Data Platform Architecture

Designing modern data platforms for scale and flexibility.

Modernization

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Data

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