Last week, over 130 data professionals tuned in to hear Kai Wolffram, Head of Analytics at TUI Group, share his lessons learned from TUI’s journey to the cloud. During the webinar, Kai spoke about the challenges he and his team encountered when trying to find the right home for their data. He also talked about the technical requirements they would need to consider to extract, load, and transform their data for analytics.
TUI, the largest tour operator and leisure company in the world, is well known: it has 70,000 employees and 27 million customers worldwide. With so many divisions and departments under the hotel and resorts umbrella, Kai and his team were looking to create consistency in their data models for analytics and reporting purposes. As they began to evaluate solutions, they sorted through the obstacles and requirements for implementation, for both their IT environment and the overall business.
Technical challenges: Failures and delay
Kai was faced with figuring out how to migrate to the cloud and, once there, facilitate faster analytics and reporting.
Their technical challenges included:
- Speed – It was simply taking too long to finish large product builds. Additionally, the analysis of new data was taking several hours to days to run SQL.
- Storage– Due to lack of storage, the team was constantly making tradeoffs to determine what data they could keep. Moreover, jobs were failing because of insufficient space.
- Scale– In TUI’s architecture, there was no capacity to increase existing jobs.
- Redundancy– When the warehouse was down, teams waited days until the issue was resolved – and lost data while offline.
Overall business challenges:
In addition to technical challenges, there were business challenges inside of TUI that had to be addressed in order to go from data-driven to data insights. These included:
- People – Just three people in the organization did all the work of operating the data warehouse, doing the development, and handling support.
- Budget – The team was working with limited IT funds, which meant that they could not bet big and be wrong – they needed to start small and calculate risks.
- Internal knowledge – The technical knowledge about current systems was completely external, with no documentation available.
- Time– TUI needed to show value in just a few months.
How did TUI reconcile these challenges with their overall vision of having an ultra-scalable, fast, simple, and cost-effective modern data analytics landscape?
View the webinar on-demand for a deep dive into the modern tech stack TUI evaluated and implemented that helped them to:
- Consolidate multiple data sources including Google Analytics, external data like Currency Exchange, PMS TML, ROB, TBL, and more.
- Orchestrate and schedule different source systems with Matillion
- Implement complex business logic and create parameterized, reusable shared jobs
- Use Snowflake’s fast and stable backend to minimize infrastructure and maintenance concerns
To learn more about how Matillion ETL software can help you modernize your tech stack and transform data for faster time to insight, get a demo.