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DataOps.liveFeb 20, 2024 8:01:49 PM3 min read

Revolutionizing pharmaceutical Data Management with DataOps: top 5 benefits for Data Engineers

In the fast-evolving healthcare industry, efficient data management isn't just a luxury; it's a necessity. Adopting DataOps, particularly through platforms like, is going to be pivotal in transforming how the health tech sector handles data.  

Omar Khawaja, Global Head of Business Intelligence at Roche Diagnostics, implemented to gain efficiency and agility. “You can’t carry on doing the same things and expect different results,” he told us. “We wanted to move the needle further on the dial and become a more agile data-driven business, which led to a pioneering data mesh and true DataOps approach.” 

And it worked... Roche was just awarded IDC's Future Enterprise Best in Future of Intelligence EMEA Award. The award recognizes Roche's data mesh strategy for delivering insights at scale and developing a data culture. Its data platform transformation has enabled them to build over 200 new data products, resulting in over $50M in benefits. 

Worldwide, Roche Diagnostics has installed 100,000 diagnostics platforms which run 27 billion tests per year. As you can imagine, data plays a huge role in this business. 

 Let's dive into the top five practical benefits of DataOps, backed by results at Roche Diagnostics and other customers. 

  1. Accelerated MVP Development and Releases—Rapid development and release cycles are critical in the medical research industry, where innovation is about more than market competitiveness. Faster innovations can directly affect patient care and outcomes.

Developing and iterating a data product, even a minimum viable product (MVP), typically takes months. DataOps is changing that experience for data engineers across industries.  

Roche Diagnostics has slashed the average MVP development time from six months to a mere 6-8 weeks. They’ve gone from releasing one every three months to over 120 per month.  

“It’s about speed,” says Paul Rankin. Head of Data Platforms at Roche Diagnostics. “The quicker you can get information to the people making the decisions, the better we can fulfil our promise of giving patients what they need next.” 

  1. Enhanced Collaboration and Sharing—Collaboration was a key aim for Roche Diagnostics when choosing a data mesh. The organization needed a federated approach across hundreds of developers and more than 20 data product teams. “We knew we’d need a powerful tool so developers could follow a DevOps methodology,” says Rankin. “The data is continuously changing, and the pipeline is continuously questioned. This could never have been done with a centralized approach.” fosters an environment of enhanced collaboration. Roche now reports heightened data awareness and sharing of best practices across teams. 

  1. Governance and Compliance without Sacrifice—Compliance is paramount in the highly regulated medical industry. stands out by providing robust data governance, as Roche's experience demonstrates. The platform's centralized policy definitions and enforcement ensure compliance with the strict data privacy and security standards essential to operating in highly regulated industries. For data engineers, this translates to a reliable framework for managing data governance without sacrificing agility.  With a structured governance framework ensuring adherence to regulatory requirements, data engineers have greater freedom to innovate.
  2. Operational Efficiency and Time Savings—DataOps drives efficiency. “We started from zero and began putting significant deliverables in the hands of users after only nine months,” says Khawaja. Another customer, data communications company OneWeb, implemented and created a scalable data hub in just six weeks. Efficiency at this level is invaluable for data engineers dealing with large datasets, allowing them to manage extensive data projects more effectively, reduce operational delays, and concentrate on core analytical tasks.
  3. Data Democratization— democratizes data, promoting a healthy data culture across the organization. For data engineers in the medical industry, from diagnostics to pharma, this democratization means easier access to diverse data sets. The ability to easily cross-reference datasets is vital for complex R&D activities. In Roche's experience, establishing a data mesh enabled data product teams to work more autonomously within a structured governance framework. This improved speed in meeting internal and external demands.

DataOps and offer a transformative approach to data management in the healthcare and pharmaceutical industry. By enabling faster development cycles, fostering collaboration, ensuring robust governance, improving operational efficiency, and democratizing data, proves to be an indispensable tool for data engineers. As health tech continues to evolve, innovative data management solutions will be key to staying ahead in a competitive and regulation-intensive field.  

Get a demo of today and find out how you could build the next award-winning data infrastructure and culture.