Data Architecture Consulting
Modern businesses need data architectures that connect their systems, support analytical workloads and adapt as business requirements evolve. The right architecture helps establish a reliable foundation for data integration, processing, reporting and decision-making.
Big Data Technologies helps businesses design and modernize data architectures around scalability, reliability, performance and practical business requirements.
Our Capabilities
From new architecture design to modernization, we help define how your data moves, is managed and supports business applications and analytics.
Create a practical data architecture aligned with your business objectives, data sources, analytics needs and technical environment.
Plan lakehouse architectures that bring data lake flexibility together with the management and analytics capabilities needed for dependable data use.
Design data warehouse foundations that support consistent reporting, analytical workloads and trusted business information.
Evaluate existing data platforms and develop a phased approach to address architectural limitations, technical debt and changing business needs.
Design Principles
Effective data architecture is not just about selecting technologies. It is about making informed decisions that balance technical requirements, operational needs and business goals.
Plan for growing data volumes, workloads and analytical demands without unnecessary complexity.
Design data flows, dependencies and recovery approaches that support dependable operations.
Align storage, processing and access patterns with workload and query requirements.
Connect architecture decisions to business outcomes, reporting needs and operational constraints.
When to Engage
Architecture consulting can help when your data environment is becoming difficult to scale, maintain or align with changing business needs.
If you also need help building the pipelines that implement your architecture, explore our Data Engineering Consulting Services. To identify risks in an existing platform, see our Data Platform Health Check.
Our Process
We use a structured approach to connect architecture recommendations with your existing environment and implementation priorities.
Understand your business objectives, current data systems, data sources, workloads and constraints.
Identify architecture gaps, integration challenges, performance limitations and modernization opportunities.
Define the target architecture, key data flows, technology considerations and implementation priorities.
Document recommendations, evaluate trade-offs and establish a practical roadmap for implementation.
Common Questions
Data architecture defines how data is collected, integrated, stored, processed, governed and made available to applications, analytics and business users.
A data architecture consultant evaluates existing systems, identifies technical and business requirements, designs target-state architectures and recommends practical implementation or modernization steps.
A data lake typically stores data in a range of formats, a data warehouse is optimized for structured analytical workloads, and a lakehouse combines aspects of lake-based storage with capabilities intended to support managed analytics. The right approach depends on your workloads, governance needs and existing environment.
Yes. An engagement can include reviewing legacy systems, documenting dependencies, identifying limitations and defining a phased modernization roadmap based on business priorities and technical constraints.
Start with a discussion about your current architecture, business goals, technical challenges and expected outcomes. We can then discuss a suitable assessment or consulting scope.
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Whether you are designing a new platform, planning a warehouse or lakehouse, or modernizing an existing architecture, let's discuss your requirements and identify a practical path forward.
Discuss Your Data Architecture Project