Cancer takes millions of lives and costs billions of dollars. One of the big problems is the expense and waste in pharmaceutical R&D efforts. Redbasin Networks has begun to attack this problem from a software and big data perspective, achieving success through an agile or fast-failure mindset. While they face significant challenges managing heterogeneous and expensive big data sets about cancer, they have been able to capture insight from automated algorithms—doing analysis in 8 hours instead of man months of largely manual effort. At last year’s SpringOne 2GX, they shared their company background, the challenges with cancer data, a working data model, and how the Redbasin analytics platform uses Spring, Redis, Neo4J, MongoDB, and more.
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