Cost savings as a result of virtualization
Stardog’s virtualization capabilities eliminated the need for expensive ETL processes, redundant data storage, and data conversion.
Increased analyst efficiency
Boehringer-Ingelheim’s knowledge graph allows analysts to reuse past research and find answers more quickly.
Increased bioinformatician output
Scientists are now able to quickly answer questions that link data from one domain to another without spending time cleaning data or creating additional local databases
Boehringer Ingelheim recognized the need to connect data from disparate parts of the company to increase research and operational efficiency, increase output, and ultimately accelerate drug research. Using Stardog to build an enterprise knowledge graph has allowed bioinformaticians and analysts to quickly and easily access the full body of institutional knowledge, all while providing cost savings.
Boehringer Ingelheim had many teams of researchers working independently to develop new treatments. But data was often siloed within teams, making it difficult to link targets, genes, and disease data across different parts of the company.
The team tried several different tech stack approaches. Some teams had built data lakes, but inadequate virtualization capabilities necessitated ETL pipelines to move data. Others had worked to predefine all requirements from scratch in an RDBMS, but that approach couldn’t support the necessary levels of complexity or flexibility.
Ultimately, they realized that they needed a bigger approach that would establish a technical foundation to enable data sharing across the entire company. This approach needed to link data from across teams, support ontologies to understand how terms related to one another, and have the flexibility to allow them to connect internal experimental results with external publicly available data of varying quality and formats.