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Global healthcare company Novartis is using Snowflake technology as a platform to streamline business processes and quickly launch life-changing drugs.
Loic Girard, global head of digital platforms and product delivery at Novartis, explained to VentureBeat how the company first adopted Snowflake in 2017. The company is using technology as part of an organization-wide data and digital initiative called Formula One, which aims to digitize operations and bring data to the heart of its business processes.
Novartis employs 2,000 data scientists who use the company’s integrated data platform to support activities ranging from research into new drugs to insights that help improve operational performance.
The company continues to explore how technology can be used to leverage new opportunities and recently joined Snowflake’s newly-launched Healthcare Data Cloud, which aims to create an integrated and cross-cloud data platform.
Here, Giraud explains to VentureBeat how Novartis places snowflakes at the center of its integrated data stack and how it uses this platform to drive insight-generation processes.
VentureBeat: What business challenge did you want to address when you adopted Snowflake in 2017?
Loc Giraud: “In the past, technologies had to do everything from beginning to end – ingestion, curation, integration. But I think as we move forward, you will see the specific role of specific data technology in your organization. Businesses want to have access to their own data and do their own thing. So, we tried to establish a self-service, abstract level through Snowflake that could go and get our data and then employees could use their own tools to analyze the data or generate insights. Our use of Snowflake is about helping our employees generate data and then embed that information into other business processes. ”
VentureBeat: Why did you choose Snowflake over other tools on the market?
Geraud: “Our Formula One platform is the best of the best – and Snowflake is part of that architecture. When we embarked on this journey of the cloud, and tried to build our data platform, we discovered a range of capabilities. For each capabilities, we looked at whether the native cloud provider could provide the capabilities that support the feature set we need. We evaluated different solutions differently. And we decided to use Snowflake in our refinement layer, which is about creating aggregated data to meet specific purposes. But over time, that is likely to change – and, as a product, snowflakes have evolved, so we started in one area, but are now being used in other areas. “
Venturebeat: How do snowflakes integrate into your day-to-day processes?
Geraud: “It simply came to our notice then. So, we’re using it for analytics generation – we use data in big data platforms like AWS or Azure. Snowflakes can work on multicloud. The other thing we do is prepare data to generate insights into a variety of use cases, such as research and development, incentive returns for sector representatives, sustainability goals, and financial goals. Another thing is that we are using Snowflake Data Marketplace to integrate information from other sources. So, in the process we had we would buy data sets from different vendors and then we would integrate that information through API on our platform. But with the data marketplace, some of the third-party information we need – such as market and industry data – is already available. “
VentureBeat: How easy is it to create an integrated data stack?
Geraud: “It takes time, I think. We have been running our Formula One program for three years now and it takes a lot of investment from my side and also from the business side in terms of finance and human resources. I think the main problem is that the technology is relatively fast. So, how do you get to the level of maturity, where you can start giving results, and on the other hand, how do you avoid technical debt? Before you wait for the tech stack to be fully ready, then the business has moved elsewhere. So, you need to constantly update your capabilities in the stack while you are distributing the value. And in our case, we split the two – our We have a platform team, and we have use-case based teams, and then these teams meet somewhere in the middle, so that the platform can distribute the roadmap, while the use case delivers the result.
Venturebeat: How do you plan to develop your use of snowflakes in the coming months?
Geraud: “Scale, scale, scale – we have a huge pipeline of use cases and products that we want to build. We are not only multicloud, but we are also multi-region. So, we have a region in Europe and the US, and we in China. Implemented our data solution. Snowflake is not yet present in China, but we hope it will come soon. We can. “
VentureBeat: What does it mean for your company to join Snowflake’s Healthcare Data Cloud?
Geraud: “We plan to work with other organizations in healthcare to develop industry standards. One of the things we are thinking about is, ‘Can we come up with a solution with other partners that anyone can use?’ The other thing we’re thinking is, ‘How do we connect our data ecosystem with prescribers, suppliers and other pharmaceutical companies?’ There are too many connections in the system to be integrated and connected to each other. You can add more value to the patient if you are able to connect the entire supply chain. I believe that if you can share your information openly, there is a lot for everyone to win. “
Venturebeat: What else do you want to achieve in the next 12 to 24 months?
Geraud: “We’ve built our Insight-Generation platform and now I’m trying to build Formula One as the company’s digital ecosystem. Therefore, I would consider integrating automation, blockchain and self-service development solutions to create a truly digital ecosystem for the organization. We run 500 drug trials a year. It is important that we can answer key questions, such as, ‘Where do we invest our money, in what trial and at what time should we decide to continue or stop that trial?’ These are activities that are now driven by business processes supported by the data platforms we have created. ”
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