Amit Satoor from SAP interviewed at Strata Rx 2013
summary
Claims use of SAP HANA in-memory to load whole datasets and combine clinical, genomics and lifestyle data so analysis happens at clinical timescales rather than weeks. Ingestion includes sequencing output and real-time lifestyle event streams; engineers apply partitioning and compression to enable in-memory ML, predictive and text analytics across structured and unstructured inputs. Goal is to surface risk signals — for example predicting violent behavior from social patterns — by integrating disparate data sources.
AI-written summary · about
chapters (8)
- 0:00Introduction
- 0:28Big data in health care
- 0:51Peoples emotions
- 1:13Technology stack
- 1:52HANA
- 2:10Future of SAP HANA
- 2:54Predictive and prescriptive analytics
- 3:18What would you solve with data
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