Unifying Data Platforms with a Federated Lakehouse
Cloudaeon streamlined a fragmented multi-platform ecosystem by building a federated Lakehouse, cutting storage costs by 40% and accelerating analytics.
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Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged.
Considering the pace at which data environment is expanding, many organisations with managing data across disparate platforms lead to silos. This exactly was the case for a large organisation that operated with a complex data ecosystem spanning Databricks, Snowflake and Microsoft Fabric.
The main issue was data duplication as teams were forced to copy datasets between platforms that lead to exploding storage costs and a lack of a single source of truth.
The need to constantly switch between systems to access different data types was hindering productivity and cross-domain analytics.
The core challenge was to unify these diverse platforms into a single and cohesive analytics environment without sacrificing their unique capabilities.
Challenges
Data silos & duplication: Running three different platforms led to 56 TB of duplicated data thereby increasing storage costs and lacked single source of truth.
Operational inefficiency: The users wasted time switching systems and validating consistency instead of analysing insights.
Governance gaps: Each platform had its own security model which made unified governance nearly impossible and creating compliance risks.
Integration hurdles: Limited mirroring features meant Snowflake objects weren’t fully supported in Fabric. This forced custom sync processes that added more technical debt.
Solutions
Cloudaeon designed a federated Lakehouse architecture with Fabric as the central hub for:
Data standardisation: 120 TB of structured data was converted into open Delta format that enabled Fabric to access it directly without duplication.
Centralised mirroring: Native Fabric mirroring unified Snowflake and Databricks data, while custom pipelines ensured real-time synchronisation where native tools fell short.
Unified governance: Using Microsoft Purview, the team cataloged 2,500+ assets and enforced consistent access policies across the ecosystem.
Streamlined analytics: Fabric became the single workspace for analytics, where the semantic models enabled consistent reporting and faster dashboarding.
Impact
Cost efficiency: Saved over $50,000 with 40% reduction in duplication storage and cutting analytics time in half.
Stronger governance: Over 90% of assets were onboarded with clear lineage and access controls where 120+ users adopted the new framework.
Better user experience: All data could be accessed data through one platform which improved collaboration and eliminated need to toggle across systems.
Strategic advantage: The open and federated design ensured scalability, interoperability with future tech with a robust foundation for advanced analytics.
Conclusion
By implementing a federated Lakehouse, the organisation transformed a fragmented environment into a unified and governed analytics platform.
Once considered an obstacle, data silos became an opportunity to establish a single source of truth.
Cloudaeon’s solution, proved to be a game changer that reduced costs, provided faster insights, built stronger compliance and a foundation which was ready to power the company’s next stage of innovation.
Ready to eliminate silos and unify your data platforms? Contact us today to explore how a federated Lakehouse can transform your analytics.
