About Client:
A renowned global hotel group with a wide portfolio of luxury resorts and business hotels, managing millions of guest interactions each year across multiple destinations.
The company operates a complex digital ecosystem supporting reservations, guest services, loyalty programs, and operational analytics. With the rapid expansion of data-driven initiatives, the organization required stronger governance capabilities supported by modern data lineage tools on Azure environments to maintain trust in its analytics platform.
Background:
The client had already adopted Microsoft Azure as its core data platform. Data from Property Management Systems, Central Reservation Systems, CRM platforms, and digital engagement tools flowed into Azure Data Lake, Azure Synapse Analytics, and Power BI dashboards.
Azure Data Factory and Databricks orchestrated and transformed the data used for reporting, operational analytics, and guest experience optimization. This cloud-first architecture enabled scalability and flexibility for growing analytics needs.
However, as pipelines and analytical use cases expanded, a critical governance capability began to lag behind: data lineage. Teams lacked clear, end-to-end visibility into how data moved through the environment. Without an effective Azure data lineage tool, it became difficult to track how datasets were sourced, transformed, and consumed across the analytics stack.
Challenge:
- Lack of Data Visibility: Teams couldn’t trace where data came from or how it was transformed, making it difficult to trust metrics.
- Slow Impact Analysis: Identifying which reports were affected by system changes or pipeline failures could take days.
- Compliance Risk: Without a clear audit trail of how personal data was processed, meeting GDPR and CCPA requirements was a growing concern.
- Low Data Literacy: Business users often misunderstood or misused data due to unclear definitions and lack of documentation.
- Manual Metadata Management: Data definitions were spread across PDFs, spreadsheets in different systems making it inconsistent and difficult to maintain
- Troubleshooting Was Painful: Diagnosing report discrepancies required time-consuming back-and-forths between teams.
These challenges highlighted the need for an enterprise-grade solution using modern data lineage tools Azure platforms that could automatically capture lineage across the organization’s data ecosystem.
