Data Modeling in Looker
Quick iteration and reusability of metric calculations for powerful data exploration. At Looker, we want to make it easier for data analysts to service the needs of the data-hungry users in their organizations. We believe too much of their time is spent responding to ad hoc data requests and not enough time is spent building, experimenting, and embellishing a robust model of the business. Worse yet, business users are starving for data, but are forced to make important decisions without access to data that could guide them in the right direction. Looker addresses both of these problems with a YAML-based modeling language called LookML. This paper walks through a number of data modeling examples, demonstrating how to use LookML to generate, alter, and update reports—without the need to rewrite any SQL. With LookML, you build your business logic, defining your important metrics once and then reusing them throughout a model—allowing quick, rapid iteration of data exploration, while also ensuring the accuracy of the SQL that’s generated. Small updates are quick and can be made immediately available to business users to manipulate, iterate, and transform in any way they see fit.