Integrating Biomedical Data through Human + Machine Intelligence

Presenting A New Approach to Taming Biomedical Data Variety

Tamr Field Engineer Timothy Danford, Ph.D., discusses how Data Variety — the natural, siloed nature of data as it’s created — is creating a bottleneck to biomedical data analytics. Rule-based, deterministic data unification approaches are “too brittle” to scale to the hundreds or thousands of different data formats, sources and silos within the enterprise. Danford submits, instead, that Tamr’s bottom-up, probabilistic approach with “active learning” is proving successful at unifying heterogeneous data at scale.

Danford-final About Timothy Danford, Tamr Inc
Timothy Danford has over a decade of experience in genomics and bioinformatics, having started his career at Massachusetts General Hospital’s MIND Informatics group. Prior to MGH, Timothy was an application architect focused on tactical genomic data integration and visualization projects at Novartis’s Institute for Biomedical Research. Timothy received his PhD in Computer Science and Artificial Intelligence at MIT.