A major North American mountain resort operator managing dozens of destinations through acquisitions and partnerships needed to understand the value of its flagship multi-resort pass to partner properties and track incremental revenue streams. Its corporate Marketing Analytics team faced a data access barrier that limited their ability to resolve these strategic challenges:
We delivered a three-part solution: an on-site Strategy, Vision, Roadmap (SVR) engagement to align on requirements, a dedicated data warehouse in Snowflake built for AI readiness, and a suite of Tableau dashboards to operationalize the insights.
The Marketing Analytics team became self-sufficient with a small group of internal analysts taking ownership of Tableau dashboards and responding to new reporting requests using the templates and patterns provided. The plain-language warehouse design delivered lasting value: when the client decided to move reporting toward Snowflake Cortex, no expensive semantic layer work was required. The data was already in the right shape, allowing the client to plug in AI capabilities immediately while the warehouse continues to serve as the foundation as tools evolve.
If your organization is consolidating properties or brands, or growing through acquisition, you may face the same data access and trust challenges shown in this engagement. Whether you manage multiple locations, track membership or subscription churn, or are planning to leverage AI for analytics, this approach applies. By designing your data foundation for AI readiness from the start, you avoid costly re-architecture when tools change. A well-documented, plain-language warehouse keeps working for years, through platform changes, and positions your team to move quickly when new capabilities emerge. More importantly, it enables your internal analysts to own their reporting without ongoing dependency on external resources.
A cross-functional team of data architects, consultants and strategists delivered both the technical architecture and managed stakeholder relationships across the organization to ensure adoption and long-term maintainability of the data foundation and dashboards.
A private equity-backed software group with independent subsidiaries on different systems needed unified reporting without sacrificing the ability to demerge individual units in the future. InterWorks delivered a multi-account data platform architecture that consolidated group-level analytics while preserving demerger readiness and enabling board-level visibility into cross-unit metrics.
A health insurer modernizing its data platform with Snowflake and dbt needed to validate foundation and derivative models before production, but lacked independent testing capability to maintain rigor.
A global hardware manufacturer evaluated options for migrating from core-based Tableau Server to Tableau Cloud as its existing infrastructure reached the end of its lifecycle.
Interworks GmbH
Ratinger Straße 9
40213 Düsseldorf
Germany
Geschäftsführer: Mel Stephenson
Kontaktaufnahme: markus@interworks.eu
Telefon: +49 (0)211 5408 5301
Amtsgericht Düsseldorf HRB 79752
UstldNr: DE 313 353 072
