A summary of talks from our first Data Mesh Days event
On Thursday, May 11, we hosted our first-ever Data Mesh Days event with a focus on data mesh implementations and best practices for life sciences. Every domain in life sciences – from drug research to supply chain and commercial teams — relies heavily on data. The data mesh approach empowers domain experts to be accountable for and better leverage their data while sharing it with others to increase innovation and evidence generation, among other benefits.
Hosted by the Data Mesh Learning community, Data Mesh Days provide a vendor-neutral space where data leaders and practitioners can gather to share and learn about data mesh. Each event will focus on a different industry; this one was Life Sciences, and our next will be Financial Services.
Our inaugural Data Mesh Day event included five presentations and a breakout session for attendees to meet each other and share learnings. Here’s a quick recap of the presentations, and you can view the full recording of Data Mesh Day here.
“Two Years of Data Mesh at Roche Diagnostics”
Omar Khawaja shared how Roche Diagnostics uses data mesh to improve stocking, procurement, and the overall impact for patients and customers. Khawaja stressed the importance of putting at least a little effort into all four data mesh principles and finding a balance–versus focusing on just one or two–to ensure you experience the true benefits of data mesh. Below you can see a snapshot of outcomes of Roche’s two-year journey into data mesh, which includes 50+ operational data products following FAIR principles, average MVP time of 6-8 weeks, 291 releases in a single month (versus one release in two weeks) with coverage for 14+ data domains:
“The Federated Data Governance Journey”
Mariana Hebborn, Ph.D., led the second talk on data governance. Hebborn is the Healthcare Data Governance Lead at Merck Gruppe. She illustrated the importance of change management — focusing on people and prioritizing conversations and missioning — when implementing any digital or data transformation. She advised data-driven organizations to invest in data governance up front, inspire stakeholder participation, and clearly define processes and procedures to empower project contributors.
“Data Mesh Strategies in Pharma and Life Science”
Ammara Gafoor from Thoughtworks and Antonio Agudo from Roche Diagnostics led the third discussion, sharing their experiences with data mesh, including common challenges and how to mitigate them. They both agreed that widespread support for data mesh depends on its ability to connect data to value. They recommend working backward from organizational goals to identify high-value analytical use cases, and ultimately, identifying which data products are needed to bring the use cases to life.
“The Real-World Data (RWD) Store: Accelerating Evidence Generation with Data Mesh”
In the fourth session, Alexandra Grebe de Barron explained how Bayer has fully embraced “data as a product” with its RWD Store, a human- and machine-friendly self-service shop that facilitates real-world evidence generation across the life-long patient pathway. The company adopted a data mesh approach to design data products that serve many users instead of niche tools or applications. As a result, they now prioritize the user experience so that their data products are easy to use, understandable, accessible, secure, interoperable, trustworthy, and valuable. Below, you can see the success of Bayer’s RWD Store by the numbers.
“Implementing Federated Computational Governance with Metadata-driven Automation”
For our last speaker session, Amber Hilton and Thinh Ha from Google Cloud explained how embedding metadata quality and governance in developer workflows can enable the data mesh and allow for automation that enables companies to scale. For organizations new to data mesh, Ha recommends first focusing on how you can empower your data teams to deliver value faster and more frequently for your customers, then working backward to identify and adopt specific data mesh principles that will help you reach your goals.
Insights + Takeaways
A common theme throughout the day was the need for organizations to inspire and incentivize people to participate and contribute to data mesh. Data mesh is a multi-year journey, so data leaders must explain why data mesh matters to get the buy-in and collaboration needed initially but also keep contributors inspired throughout the process.
Data Mesh Learning community Resources
- Engage with us on Slack
- Organize a local meetup
- Attend an upcoming event
- Join an end-user roundtable
- Help us showcase data mesh end-user journeys
- Sign up for our newsletter
- Become a community sponsor