This document discusses scaling topological data analysis (TDA) using the Mapper algorithm to analyze large datasets. It introduces Mapper and its computational bottlenecks. It then describes Betti Mapper, the authors' open-source scalable implementation of Mapper on Spark that achieves an 8-11x performance improvement over a naive version. Betti Mapper uses locality-sensitive hashing to bin data points and compute topological networks on prototype points to analyze large datasets enterprise-scale.