Although new tools and technologies, ranging from cloud data warehouses to collaborative notebooks, have displaced their predecessors, SQL remains unchallenged as the lingua franca of analytics professionals. Malloy, however, seeks to unseat SQL by unifying querying and semantic modeling into a single language. In this post, Carlin Eng, the Head of Data Engineering at Eppo, provides an overview of Malloy and describes how it enables fast iteration. He first defines the “semantic layer” as “codify[ing] domain-specific logic on database tables” and postulates that LookML was not widely embraced by data scientists because it may have impeded rapid data exploration. Next, he discusses a few noteworthy features that enable users to interleave data modeling and data analysis when using Malloy.