Client Background
The client is a well-known company in the travel and leisure industry, boasting more than 1,000 employees. Due to a non-disclosure agreement (NDA), further information cannot be disclosed.
Challenges
Centralized data team bottleneck
The company’s rapid growth affected the central data team, creating a bottleneck. With around 30 teams generating massive data, the central team couldn’t manage efficiently, slowing progress.
Lack of business context
The central team lacked business context and couldn’t respond quickly to data requests, blocking teams needing timely data access.
No decentralized data ownership
To resolve the bottleneck, data ownership shifted to individual teams. Each team would manage its own data, pipelines, and quality, despite not being data engineers.
Data quality and unmet needs
Ongoing data quality issues and unmet business needs drove the push toward decentralization, improving responsiveness and accountability.
Our Solution
Decentralizing data management
To decentralize data while maintaining a single source of truth, we addressed key technical and strategic questions, including selecting the right data warehouse and ensuring teams understood their responsibilities for data quality and business logic.
Establishing governance and policies
We implemented data ownership and governance policies to manage expanded data access across teams, focusing on protecting sensitive data and training teams to meet quality standards.
Overhauling data quality
We replaced an outdated data quality tool with a new framework including not just tools, but also better processes and collaboration.
Managing the technical transition
The technical shift, such as migrating to a cloud warehouse, required a broader change in mindset. Data governance played a crucial role in ensuring quality information across teams.
Treating data as a product
Teams were made accountable for the data they shared, treating it as a product. We encouraged communication between data producers and consumers to align expectations and responsibilities.
At a Glance
Challenges
- Inefficient data management leads to bottlenecks that obstruct company growth
- Lack of business context for timely data requests resolution
- Inadequate data ownership across teams
- Persistent data quality issues impacting decision making
Solution
- Shifted to decentralized data ownership for better data management
- Implemented data governance by establishing new roles and responsibilities across all relevant teams
- Developed a new data quality framework focused on cooperation and prevention
- Enhanced cross-team collaboration for effective communication
