Founded in 2004 in Dublin, Ireland, CarTrawler is the Human TravelTech company and leading B2B provider of solutions for the travel industry. Employing over 400 people, CarTrawler designs, builds, and powers customized solutions for brands including EasyJet, Eurowings, and United Airlines, to help offer car hire products to their customers. The CarTrawler and Soda story exists based on the shared vision to put data-driven innovation and human connection at the heart of operations.
CarTrawler prices over a billion different car hire products every day for airlines, travel agencies, and travel websites. Doing this effectively is something which requires huge volumes of data, advanced algorithms and, critically, control over data quality. However, with a data strategy influenced by individual departmental needs with separate data rules across disparate systems, the synchronization of data changes across teams had become a highly-resource intensive process. Coupled with the acquisition of several major customers in the travel industry, CarTrawler urgently needed to identify ways to scale up its data operations.
Initially embarking upon a data transformation by building its own data quality tool, the company soon realized it was still unable to scale fast enough to on-board further new clients. In addition to the problem of scalability, CarTrawler also needed to overcome two major data quality challenges which its in-house tool couldn’t solve: firstly, a lack of self-serve functionality for business users to take data quality into their own hands; and secondly, the need to automate the implementation of checks to swiftly identify and then resolve issues with the data.
CarTrawler selected Soda to deliver a scalable data quality solution which would enable its data engineers to test data quality as-code and prevent data issues, and empower its data consumers to self-serve and manage their own data quality expectations. The team was immediately delighted by the speed and ease at which they could migrate to Soda, swiftly implementing Soda in parallel with Snowflake, and providing a single source of truth across the entire business.
Today, Soda has been fully integrated with CarTrawler’s existing technology stack - including Airflow, dbt, Snowflake, and AWS, to store, ingest, and transform the data, Snowplow for customer data management, and Tableau and Thoughtspot for BI - which has been carefully curated to deliver self-serve capabilities. Using Soda, CarTrawler has established a low-code environment for data consumers across its organization to define data quality agreements and easily write data quality checks using SodaCL, Soda’s domain-specific language for data quality checks.
Soda has become an integral part of CarTrawler’s daily data operations. It enables the engineering team to test and monitor data pipelines and ensure the delivery of complete and accurate data that is fit for purpose. Business teams have access to the self-serve capabilities they need to solve data quality issues themselves rather than having to wait for an available analyst. Meanwhile, data scientists are empowered to focus solely on building models, leaving the bulk of repetitive testing and data quality tasks to Soda.
With the capabilities provided by Soda, CarTrawler has generated total trust in the huge volumes of data it is ingesting and providing to its users, at scale. Access to better quality business and analytics models has improved critical business decision-making across the organization. Ultimately for CarTrawler’s business, the enhanced trust in the data feeding its real-time recommendation engines has delivered a 5% improvement in revenue per visitor.
"Combining Snowflake and Soda has led to a wealth of benefits for us, meaning that not only have we been able to create a single source of truth for data analytics and data science, but we can trust the data contained in that platform thanks to being able to easily apply data quality rules, see feedback on those rules and implement fixes to achieve the best level of data reliability. The two platforms work in complementary ways, providing a combined solution which has taken our data operations to the next level." Patrick Callinan, Director of Insights and Data Science