Current-state assessment
Capture the current environment, dependencies, constraints and operating risks so decisions about current-state assessment are based on what actually exists.
Data & Analytics
Data Architecture & Modernization
Gromnii modernizes fragmented data estates without losing operational continuity.
Sources
Ingest
Quality
Platform
Insight
Action
When this is useful
Use data architecture and modernization when information is fragmented across legacy stores, duplicated models or brittle pipelines that cannot support new analytics and AI requirements. Modernization should preserve data meaning and operational continuity while simplifying how data is stored and served.
How information moves through the system
This reference shows one possible Data Architecture and Modernization arrangement. The actual design depends on the systems, constraints and controls involved.
01Inventory
02Target state
03Migration waves
04Validation
05Cutover
06Retirement
What Gromnii builds
Target data architecture
Define authoritative domains, integration patterns, analytical serving layers and governance boundaries before moving data so the new platform has a clear operating model.
Coexistence & migration
Map application, data and integration dependencies before migration and coexistence work begins.
Schema modernization
Replace brittle legacy structures with stable business definitions and versioned schemas while preserving the mappings needed for phased migration.
Cutover planning
Stage Cutover planning so old and new paths can be reconciled while critical work continues.
What matters in production
Data integrity
Compare source and target counts, keys, relationships and business totals during migration, and resolve mismatches before the new platform becomes authoritative.
Downtime
Plan migration windows around dependent reports, integrations and applications, with clear rules for what can pause and what must remain continuously available.
Rollback
Preserve recoverable source data and reversible migration steps until reconciliation confirms that the target architecture is producing correct results.
Ownership
Assign decision owners for source systems, target models and migration exceptions so unresolved data conflicts do not stall the modernization.
What it can improve
Simpler data landscape
Reduce unnecessary duplication and one-off movement patterns by defining clearer source, storage and serving responsibilities.
Safer migration
Plan schema changes, reconciliation, coexistence and rollback so modernizing data does not corrupt dependent reports or applications.
Better support for new workloads
Create data structures and interfaces that can serve analytics, applications and AI without rebuilding the foundation for each use case.
Related solutions and industries
Discuss a Project
Describe what Data Architecture and Modernization should change, the systems it must work with and the constraints that matter.