Developing Data Models with LookML
In this 1-day course we’re taking a look at how to build scalable, performant data models with LookML in Looker.
Developing Data Models with LookML shows you how to curate and manage data in your organization’s Looker instance, so that business users get standardized, ready-to-use data to answer their questions. You start with the Looker interface and IDE, how Looker writes SQL, the relationship between LookML and SQL, and the LookML development lifecycle, including Git-based version control from writing to deployment.
You then dive into modeling: the anatomy of a LookML project, dimensions and measures, LookML dashboards, and building Explores and filters for your users, including how symmetric aggregation keeps results accurate. The day ends with derived tables (SQL, native and persistent) and with caching and datagroups. The course includes demos and two labs, one creating dimensions and measures with LookML and one creating derived tables, plus a quiz after every module.
The course is aimed at data developers responsible for data curation and management, and at data analysts curious about how developers use LookML. Participants should have a basic understanding of SQL, Git and the Looker business user experience; if you have not worked as a data explorer in Looker, completing Analyzing and Visualizing Data in Looker first is recommended. Analyzing data in Explores, building and sharing dashboards and Looker administration are not covered.