Data Architecture Audit for OHO Group
Data Architecture Audit for OHO Group
OHO Group set out to modernize their data infrastructure. Agmis was brought in to conduct a data architecture audit - reviewing existing systems, mapping data flows, and identifying opportunities to bring everything into a unified, future-ready foundation.
A Growing Operation Ready for the Next Step
OHO Group operates a large-scale manufacturing environment with data generated across the production floor - from sensor platforms and quality control systems to energy monitoring, access control, and enterprise software. The systems were functional, but many had been deployed over time to solve specific needs, and not all of them provided data in consistent or easily accessible formats.
As the company looked to implement a centralized reporting and analytics infrastructure, the goal was clear: review every existing system and the data it produces, find all opportunities to connect that information into a common pool, and make sure nothing gets missed along the way. The audit was a proactive step - not a response to failure, but a way to ensure the next phase of modernization would go smoothly.
Reviewing the Full Data Landscape
The core systems were already in place. The question was how to bring other parts of the infrastructure into alignment - ensuring each system could contribute its data to a shared, structured environment. Agmis reviewed each component to understand what data it generates, how it's stored, and what it would take to integrate it.
Opportunities Identified Before the Upgrade
The audit surfaced areas where existing systems could be better aligned with the company's modernization goals - giving OHO Group a clear picture of what to address before moving forward.
Unstructured Data Storage
Some systems stored information in flat files with no structured format, which would need to be addressed to enable automated processing and cross-system queries in the new environment.
Isolated Data Sources
Several data sources operated in isolation with no integration path beyond manual exports - areas where establishing direct connections would unlock more complete operational visibility.
A Clear Foundation for Moving Forward
Complete Data Source Map
A comprehensive visualization of every system and its connections - showing what generates data, where it flows, and where it stops.
Architecture Vision
A recommended approach for centralizing data via API-driven integration, providing a target state architecture for the modernization effort.
Prioritized Risk & Gap Register
A ranked list of areas requiring attention before the upgrade - ensuring resources are directed where they matter most.
Next Steps
Infrastructure Updates
Where existing systems no longer meet requirements for data format, speed, or integration capability, the audit identified specific components to update - ensuring the new centralized environment receives clean, reliable data from every source.
Centralized Data Pipeline
Implement an API-first data pipeline strategy to bring all systems into a shared data pool - replacing manual exports with automated, structured data flows that support real-time reporting and analytics.
The Map Before the Journey
Modernization goes smoothly when there's a clear understanding of what's already in place. Companies that review their data landscape before upgrading avoid the costly rework that comes from discovering gaps mid-implementation.
Smooth Transition
A pre-upgrade audit ensures every system is accounted for, every data flow is mapped, and the modernization plan reflects reality - not assumptions.
Modernize With Confidence
Every upgrade decision is backed by a complete understanding of the current data landscape and its interdependencies.
Future-Ready Foundation
A unified data architecture sets the stage for automation, real-time analytics, and continued optimization as the business grows.