What Is Data Infrastructure?
Data infrastructure covers the platforms, architecture, and technical foundations used to store, move, manage, and make data available across the business. It addresses problems such as fragmented data environments, slow or unreliable pipelines, rising storage costs, poor scalability, and limited access for analytics or reporting. Typical work may include cloud and on-premises data architecture, data lake or warehouse design, extract, transform, and load (ETL) pipeline improvements, database and storage modernization, integration planning, and performance or resilience reviews. Clients may seek independent consultant support when evaluating architecture options, preparing a migration roadmap, or needing experienced guidance on trade-offs among cost, reliability, security, and future data needs.
Umbrex Practices in Data Infrastructure
- Data architecture strategy
Target data architecture, enterprise data models, governance, and migration roadmaps across fragmented platforms and business domains
- Data governance model
Data ownership, stewardship, decision rights, governance forums, and policy design for clearer accountability across critical data domains
- Data infrastructure roadmap
Target architecture definition, platform rationalization, migration sequencing, and multiyear investment planning for modern data infrastructure
- Data integration strategy
Target integration architecture, platform selection, and migration sequencing for reliable data flows across ERP, CRM, and analytics systems
- Data platform strategy
Target architecture, migration sequencing, governance, and vendor decisions for modernizing data warehouses, lakehouses, or hybrid platforms
- Data quality improvement
Data profiling, remediation planning, and governance controls to improve accuracy, consistency, and readiness of critical business data
- Data warehouse and lakehouse strategy
Target architecture, platform selection, governance, and migration roadmap for modern data warehouses, lakehouses, or hybrid analytics environments
- Master data management strategy
Data governance, golden record definitions, stewardship design, and rollout planning across customer, product, supplier, and other core data