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lastminute.com logolastminute.com

Travel firm streamlined data landscape and visibility—eliminating duplication and improving productivity and ROI with OpenText™ Analytics Database

lastminute.com logo

About lastminute.com

lastminute.com is a European travel tech leader in dynamic holiday packages, giving holidaymakers access to millions of real-time combinations. It uses technology to simplify, personalize, and enhance customers’ travel experiences.

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  • Countries:
    10
  • Employees:
    1,700
  • Staff nationalities:
    48
  • Population Served:
    8.485 Million

Summary

Challenges

  • Rapid growth drove exploding data volume.
  • Segregated data warehouse and data lake limited unified access.
  • Different tooling across environments led to duplication and heavy “glue” code.

Solution

  • Consolidated data environments for centralized access and analysis.
  • Enabled advanced predictive models on unified data.
  • Improved collaboration with a common catalog and faster queries.

Results

  • Simplified infrastructure; removed duplication
  • Prepared for containerization and automation
  • Lowered cost and increased productivity

Challenges

  • As the business scaled, so did the volume and diversity of data.
  • Separate data warehouse and data lake created a structural divide.
  • Different tools across environments drove duplication and maintenance overhead.

With operations across multiple European markets expanding and demand for real-time holiday packages increasing, lastminute.com experienced a sustained surge in data volume and variety. Bookings, web interactions, partner feeds, marketing activities, and customer support engagements all generated high-velocity data with different structures and latency requirements. This growth threatened pursuit of governance, access pattern, and time-to-insight initiatives.

Over time, the data estate evolved into two parallel environments: a data warehouse—integrated with ETL and reporting tools—and a data lake, ingesting raw data from many sources. The strict separation between the two created a divide in how data was organized, accessed, and manipulated. Different teams relied on different tooling, and a substantial amount of “glue” code emerged for data movement and orchestration. The result was duplicated datasets, higher maintenance overhead, and slower delivery of analytics and insight. As the data platform lead summarized, the separate warehouse and lake model introduced a “stark divide” that made future growth more challenging due to tooling sprawl, orchestration code, and duplication across stores.

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By removing the data divide and centralizing all data analytics in OpenText Analytics Database, we eliminated data duplication and boosted our data analysts’ productivity. We have full visibility of the data in our environment and our data-management teams collaborate more effectively as a result.

Andrea Zanetti
Data Platform Lead, lastminute.com

Solution

lastminute.com used OpenText Analytics Database (in eon mode) to consolidate segregated data environments, reduced duplication and created a more collaborative, transparent workspace for data teams.

Products deployed

Consolidating data environments for easier access and analysis

lastminute.com turned to OpenText to combine the data warehouse and data lake environments, thus removing the divide between them. A common data access platform and set of data manipulation tools would allow engineers and analysts to share a single, well-understood toolset to query and process data. Combining the environments would also eliminate data duplication and, with it, the need for a vast amount of glue logic.

“OpenText Analytics Database is a key ingredient for us to create a data lakehouse architecture,” said Zanetti. “OpenText Analytics Database in eon mode works particularly well for us, as it allows us to meet the demands associated with data intensive workloads and fast data transaction requirements, while making tangible storage savings thanks to its effective data compression.”

Introducing advanced predictive models

Introducing OpenText Analytics Database as a common interface to all data removed the need for separate data ingestion and glue logic. The complete decoupling of data from the producer and the consumer—while still maintaining absolute compatibility—further supported the “single source of truth” vision. This created an analytical solution that allows the company to correlate data from traditional BI processes with data from marketing campaigns, CRM, and machine learning analyses from the data scientists —enhancing its customer analytics with advanced predictive models.

OpenText Analytics Database ingests data from a wide variety of sources and uses this for data exploration and query purposes, as well as for reporting.

Improving team collaboration with optimized data access

The data consolidation drastically simplified the environment, which made life infinitely easier for the lastminute.com data management teams. According to Zanetti, “With optimized access thanks to OpenText Analytics Database, we were able to completely avoid unstructured data or inefficient formats. A common data catalog for all data improved team collaboration, and we were pleased to see the high-performance engine giving us faster-than-ever query responses."

A women using mobile phone

A common data catalog for all data improved team collaboration, and we were pleased to see the OpenText Analytics Database high performance engine giving us faster-than-ever query responses.

Andrea Zanetti
Data Platform Lead, lastminute.com

Results

OpenText Analytics Database paved the way for a containerized future with Kubernetes, boosting scalability and cost/energy efficiency. AI driven algorithms optimized marketing spend and improved ROI.

Simplified infrastructure complexity and deduplicated data

The infrastructure simplification saved money, time, and maintenance effort, while enabling a common pattern of access to the data. This allowed the team to remove the artificial divide between data lake and data warehouse, creating a consolidated lakehouse with a common set of query tools and language. The process removed glue logic and complexity, as well as data duplication.

Enabled the move to containerization and automation

The next step was a move towards a containerized cluster environment. Kubernetes automates deployment, scaling, and management of containerized applications. It allows advanced workload routing where instances for a data query job can be spun up and then down automatically when the job is complete. It leverages cost effective communal storage and provides the flexibility to run different kinds of analytics work—such as ELT and power dashboards—each on the ideal compute infrastructure. This delivers scalability and efficiency to do more while spending far less on compute, reducing energy usage, carbon footprint, and costs.

Realized cost savings and improved productivity

OpenText Analytics Database now plays a key role in studying customer behavior across all lastminute.com channels and analyzing every step of the customer journey—from preliminary searches to final payment. The implementation is positively impacting marketing campaign ROI and company revenue. In addition, AI driven algorithms for attribution and bidding automation help optimize marketing costs overall, leading to increased profits.

Zanetti concluded, “By removing the data divide and centralizing all data analytics in OpenText Analytics Database, we eliminated data duplication and boosted our data analysts’ productivity. We have full visibility of the data in our environment and our data management teams collaborate more effectively as a result. Our goal at lastminute.com is to enrich the lives of travelers through innovative use of technology. Our partnership with OpenText embodies this mission.”

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