Product descriptions:
DEICHMANN SE is Europe’s largest footwear retailer, operating at significant scale across more than 30 countries and serving millions of customers through a growing e-commerce business. As the family-owned company continued to invest in data as a strategic asset, DEICHMANN built a modern analytics foundation on Databricks to support reporting, analytics, and data science across the organization. The next step was activation: enabling trusted, governed data from the lakehouse to support customer marketing at scale, including activation in SAP Emarsys. With Databricks Lakebase, DEICHMANN established a production-ready bridge between analytics and customer engagement, supporting e-commerce marketing teams across Europe while reducing operational overhead for data and platform teams.
Turning a century of retail leadership into data-driven customer engagement
Founded in 1913, DEICHMANN SE has been a market leader in European footwear retail for decades. A century of innovation later, what began as a small operation serving miners in the Ruhr region has grown into Europe’s largest footwear retailer, with approximately 4,700 stores across more than 30 countries and 49,000 employees worldwide. In 2024, the company generated approximately 8.7 billion euros in revenue, offering everything from heritage brands such as Elefanten to fashion-forward collections like Graceland, premium lines including 5th Avenue, and partnerships with global brands including adidas, Nike, and Puma. Operating at this scale requires a strong data foundation to understand customer preferences, support inventory planning, and enable targeted marketing across diverse European markets. DEICHMANN invested in building a modern lakehouse on Databricks to power analytics and insights across the business, positioning the company at the forefront of retail data strategy. As data maturity increased, the next frontier became activating those insights more directly within customer marketing workflows.
“The integration gap between our data lakehouse and marketing platform required ongoing engineering intervention,” explained Kevin Haferkamp, Head of Data Platform & Engineering CoE, IT Data & Analytics. “We needed a self-service solution that would let CRM teams access the customer data they needed without constant technical support.” As DEICHMANN’s data capabilities matured, marketing teams identified opportunities to work with more advanced customer segments and behavioral attributes already available in the lakehouse. The challenge was architectural: creating a seamless connection to the customer marketing system that would allow teams to move quickly while maintaining governance and data quality standards.
Operationalizing analytics with Databricks Lakebase
The breakthrough came with Databricks Lakebase, a managed PostgreSQL database that aligned with DEICHMANN’s architectural vision. Lakebase offers an OLTP database solution directly integrated with the Databricks Lakehouse, enabling the team to serve data from their analytics layer into operational applications with minimal overhead. “We were quite excited to have a managed PostgreSQL database provided by Databricks,” said Haferkamp. “It made it very easy to spin up Lakebase and put it into production for real use cases.” Lakebase is a new category of operational database that brings transactional workloads closer to analytics and data science within the lakehouse. By integrating a managed PostgreSQL database directly with Databricks, Lakebase allows operational use cases to run alongside analytical workloads without introducing separate infrastructure or complex data movement. For DEICHMANN, this architecture enables governed data to be activated for omnichannel customer engagement across digital touchpoints while remaining part of the same data platform.
“We see the lakebase architecture as a way to operationalize our analytics data more easily,” Haferkamp added. “It allows us to use the same governed data for analytics, data science, and e-commerce marketing use cases without building and maintaining separate integration pipelines.”
Within this model, data engineers and software engineers manage synchronization logic and guardrails, while platform engineering teams focus on instance setup and governance standards. CRM teams can then work within these boundaries, triggering data synchronization to support campaign execution without relying on constant engineering support.
The Lakebase instance supporting this use case is in production across Europe for e-commerce marketing and integrates with SAP Emarsys as the downstream activation platform.
Enabling marketing agility today and future innovation
With Lakebase in place, DEICHMANN can activate a broader set of customer and product data for e-commerce marketing workflows with less operational effort than before. Previously, only a limited number of standardized data products were shared due to the effort required to maintain ongoing synchronization. Lakebase makes it easier to expand this set while preserving governance and data quality.
“Having three clicks taking maybe 30 seconds, then you have your synchronization job of a table available,” said Haferkamp. “Any other effort in programming the pipeline to sync to an external database is unbeatable.”
Today, this architecture supports e-commerce marketing use cases such as serving enriched audiences and segments backed by analytics and data processing in Databricks. Looking ahead, DEICHMANN views Lakebase as a strategic foundation that can support additional operational data activation use cases as business needs evolve.
“We will grow with use cases as Lakebase itself grows,” Haferkamp said. “We have some ideas where we would like to test Lakebase for additional use cases already in our pipeline.”
By pairing a mature lakehouse strategy with a modern operational data layer, DEICHMANN continues its long tradition of innovation. Its use of Lakebase demonstrates how established retailers can connect analytics and activation more closely, empowering marketing teams with trusted data while maintaining governance and scalability across the organization.