NoSQL databases like MongoDB are making it easier than ever for developers to quickly build complex, agile applications that scale well. Unfortunately, the rise of NoSQL has dark side: data stored in NoSQL databases is invisible to traditional business analytics and intelligence apps. As a result, operations often spends a massive amount of time and effort developing complex pipelines to transform NoSQL data into a format compatible with traditional RDBMS. In this talk, John A. De Goes introduces SlamData, a new open source project designed to build a NoSQL BI application by extending the operations and data model of relational algebra. The result is backward compatible with SQL, but allows freeform analytics on semi-structured, heterogeneous, deeply nested data. John discusses the design of SlamData and highlights some of the issues involved in bringing the project to life.