Much of the data we manage day-to-day lives in silos and, while the data within each silo can be analyzed on its own, this produces limited value for businesses. The deeper value becomes apparent when the disparate data is connected and transformed to produce patterns, insights, and predictions. This undertaking requires a significant amount of time and labor only to be susceptible to human error. As businesses are faced with analyzing big data from heterogeneous sources as quickly as possible, data integration will increasingly look to automation and machine learning for the heavy lifting. Businesses are pulling data from CRM systems, social media, apps, and a swarm of other possible sources and this data is often unstructured.