Looker is Google Cloud's enterprise business intelligence platform built on LookML, a proprietary modeling language that defines your data's semantic layer. Unlike traditional BI tools that query databases directly, Looker translates LookML definitions into optimized SQL, enabling governed, reusable data models that ensure consistent metrics across your organization. LookML's declarative syntax lets developers define dimensions, measures, joins, and access controls once — then business users explore that curated data model through an intuitive interface without writing SQL. The key insight: Looker separates data modeling from data consumption, ensuring analysts and executives work from a single source of truth while developers maintain full version control through Git integration.
What This Cheat Sheet Covers
This topic spans 23 focused tables and 98 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
Table 1: LookML Project Structure
| Component | Example | Description |
|---|---|---|
project_name: "ecommerce" | Collection of LookML files defining models, views, and dashboards; stored in Git repository for version control. | |
connection: "bigquery_prod"include: "*.view"explore: orders {} | Specifies database connection, which views to include, and defines Explores users can query; one model per database. | |
view: customers { sql_table_name: schema.customers;; dimension: id { primary_key: yes sql: ${TABLE}.customer_id;; }} | Maps to a database table or derived table; defines dimensions and measures; typically one view per file. |