Collecting and analyzing data is at the heart of every pharmaceutical R&D organization. As a result, we at Merck KGaA store large amounts of very diverse data – from assay results in early research, to operational data from clinical trials, human clinical trial data and data related to regulatory submissions. In the upcoming era of artificial intelligence (AI), making this data available to AI systems at scale is a strategic imperative. For this reason, we have formed a cross R&D workstream to modernize our compute & story ecosystem. In this presentation, we will explain the approach taken, the main challenges faced and how we are addressing them. One important component of our new ecosystem is Snowflake, where we leverage automation and blueprints to enable a consistent technical foundation across the different R&D domains.