Customer Story

Technical Enablement Boosts Roche’s Productivity and Solidifies Their Top Position in the Market


Roche — one of the world’s largest biotech companies — serves as a provider of in-vitro diagnostics as well as Alzheimer’s and cancer treatments. The company’s focus on personalized healthcare moves beyond a one-size-fits-all approach, ensuring tailored care for each patient. Today, Roche treats 28 million people yearly and employs more than 120,000 people, ensuring it holds the largest installation base of diagnostic platforms around the world.


Roche aims to harness data to shorten the time and cost of delivering valuable insights for customer understanding, product usage tracking, and more targeted and personalized marketing and R&D — ultimately enhancing customer experience, improving product performance, and boosting its visibility in the market.


Roche knew there was more they could be doing with their data, but the data team faced challenges while undergoing a cloud migration, which involved changes in their data stack and the simplification of their existing data architecture. These challenges included:

  • Need for dbt Expertise: Roche’s data team had great experience in AWS and SQL, but needed expertise with dbt. The team needed additional training in dbt best practices, including automated testing, documentation, and CI jobs. Their dbt Cloud adoption for affiliate teams was postponed.
  • Managing complexities in cloud migration: As Roche transitioned their data operations to a cloud-based environment, the data team was poised to further their expertise in AWS Redshift and dbt. This migration presented an opportunity to streamline their legacy systems and logic, aligning with the latest advancements and best practices in data management.
  • Cultivating technical leadership at the affiliate level: With Roche’s shift from local to global systems — as well as the adoption of advanced CRM and SAP systems — there was a clear avenue for strengthening technical leadership among affiliate teams. Enhancing skills in dbt Cloud, Git, and DevOps, and refining data modeling and architecture practices, were identified as crucial steps to ensure a cohesive and efficient global integration.

These combined challenges hampered operational efficiency and delayed the company’s progress toward its goals of an improved harmonized data platform.


Analytics8 became an extension of the team providing “data team as a service” functionalities including:

  • Leadership and Training: We provided leadership and comprehensive dbt training, empowering Roche’s data team to leverage dbt’s best practices and modern data technologies.
  • DevOps and dbt Cloud Enablement: To ensure the success of Roche’s local affiliates we enhanced their existing use of GitLab, migrated their affiliate data pipelines to dbt Cloud, and enabled their analytics teams to use the latter to allow for more self-sufficiency and better understanding of the development process.
  • Navigating a Complex Cloud Migration: We simplified the data lineage by transitioning from Oracle/Informatica to dbt, paving the way for seamless integration for their CRM and SAP systems. We also reduced code complexity by utilizing DRY principles and reducing the technical debt by making the code more maintainable and efficient. Finally, we ensured the code is better documented by using both Git and dbt Docs.
  • Tailored dbt Solutions: We contributed new selector methods to the dbt-core open-source code, which eliminated the need to run legacy data models and reduced pipeline runtimes. We further enhanced the pipeline runtimes by refining the SQL used, introducing distribution and sort keys, and eliminating unused business data.
  • Enhanced External Visibility and PR: We worked with Roche on securing a speaking engagement at the Coalesce conference — one of the largest global data events — to boost the team’s external and internal visibility.


Roche’s adoption of dbt best practices and enhancement of their data infrastructure have introduced benefits, including:

1.) Scalability and Market Readiness: Adhering to dbt best practices and utilizing simplified code, Roche is now better positioned for scalability and faster market entry. This includes marked improvements in data accuracy, report usability, and overall efficiency, crucial for a smooth transition to the new CRM and SAP systems.

2.) Enhanced Global and Regional Data Operations:

  • Accelerated Data Product Delivery: Revamping the backend has enabled Roche to deliver data products swiftly and efficiently across additional geographies, enhancing global presence and reducing technical debt.
  • Effective APAC Affiliate Data Integration: Focused efforts in the APAC region have led to successful integration of Global Data Products, streamlining the onboarding of new affiliates, and adopting modern data management practices. This has resulted in a cohesive and efficient data environment, improving Roche’s data insight capabilities and regional operational support.

3.) Operational Efficiency and Cost Reduction:

  • Reduced Time and Cost to Scale Data Products: The optimization of dbt models has significantly reduced the reporting layer’s time and cost burden, while improved code quality has made it more maintainable — helping to minimize scaling and maintenance expenses.
  • Decreased Pipeline Runtimes: The omission of unmodified models has led to reduced pipeline runtimes and prevented failures from legacy models.

4.) Data Integration for Germany Affiliate: The integration of SAP and CRM data for the Germany affiliate has empowered Roche’s business users to analyze client interactions and their impact on sales metrics. The migration, simplification, and enhancement of over 20 dashboards involving customer, sales, and geographical data have provided deeper insights into the operations and launch of new products.

Through strategic partnership, Roche overcame significant challenges, substantially improving their data infrastructure and cementing their position as a pioneer in personalized healthcare solutions.

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