Data Architecture Modernization for a Mid-Size German Insurer

Challenge

A mid-size German insurance company with around 2,000 employees was running its analytics infrastructure on an aging technology stack. The core platform consisted of DB2 UDB as the data warehouse database, with data sourced from an IBM host system, loaded through Talend and SAS Data Integrator, and delivered to business users via Oracle BI. The technologies were established but increasingly difficult to maintain, and the load processes suffered from performance problems that slowed down data delivery.

Beyond the technical constraints, the organization lacked formal governance over its data modeling and documentation practices. Data structures had grown organically over the years, and new team members struggled to understand the logic behind existing transformations. The business driver for the project was clear: modernize the IT infrastructure and establish proper governance around data modeling and documentation to bring the analytics platform to a maintainable, extensible state.

Approach

Alligator Company joined with a team of three consultants working alongside twelve members of the client’s internal team over a 24-month engagement. The project was structured in phases, starting with an assessment of the existing architecture and a migration plan for the transition to a new data architecture based on Data Vault.

The team introduced Data Vault as the core modeling methodology, replacing the legacy data warehouse structures with a standardized, auditable architecture. MID Innovator was brought in as the modeling tool to formalize the data model and create documentation that had previously been missing. This gave both the technical team and business stakeholders a shared reference point for understanding data flows and business logic.

On the database side, the client migrated from DB2 UDB to DB2 BLU, IBM’s columnar in-memory technology. This infrastructure change directly addressed the performance problems in the load processes: DB2 BLU’s columnar storage and in-memory processing reduced data loading and query execution times. The SAS Data Integrator continued to handle the ETL orchestration, but the underlying execution engine was now faster by an order of magnitude.

The combination of Data Vault modeling with model-driven development through MID Innovator reduced the effort required to specify and implement new data structures. Rather than building each integration individually, the team applied standardized patterns that could be defined once in the model and generated consistently across the platform. This pattern-based approach cut the time spent on design, modeling, and coding — the cost blocks where the largest share of project effort had been concentrated.

Throughout the engagement, Alligator Company transferred knowledge to the client team so that internal staff could operate and extend the new architecture independently after the engagement ended.

Outcome

The modernized architecture delivered measurable cost reductions across the analytics platform. The combination of infrastructure modernization (DB2 BLU), standardized Data Vault patterns, and model-driven development reduced total cost of ownership by 30–50%, which translated to over EUR 200,000 in annual savings.

The client also gained a documented, standardized data architecture that new team members could understand and extend without relying on tribal knowledge. The governance practices established through MID Innovator gave business stakeholders visibility into data lineage and model documentation that had not existed before.

• Total cost of ownership reduced by 30–50%, yielding EUR 200k+ annual savings
• Personnel efficiency and automation reduced effort in design, modeling, and coding
• DB2 BLU migration resolved legacy load performance issues
• Internal team of 12 enabled to maintain and extend the architecture autonomously