More of us are building apps to make sense of massive amounts of data. From public datasets like lobbying records and insurance data, to shared resources like Wikipedia, to private data from IoT, there is no shortage of large datasets. This talk covers strategies for ingesting, transforming, and storing large amounts of data, starting with familiar tools and frameworks like ActiveRecord, Sidekiq, and Postgres. By turning a massive data job into successively smaller ones, you can turn a data firehose into something manageable.