Skip to main content

Menu

LEVEL 0
0/5 XP
HomeAboutTopicsPricingMy VaultStatsPractice TestsCertifications

Categories

🎓 Certifications
🤖 Artificial Intelligence
☁️ Cloud and Infrastructure
💾 Data and Databases
💼 Professional Skills
🎯 Programming and Development
🔒 Security and Networking
📚 Specialized Topics
CheatGrid
HomeAboutTopicsPricingMy VaultStatsPractice TestsCertifications
LVLEVEL 0
0/5 XP
GitHub
© 2026 CheatGrid™. All rights reserved.
Privacy PolicyTerms of UseAboutContact

Looker and LookML Cheat Sheet

Looker and LookML Cheat Sheet

Back to Business Intelligence
Updated 2026-05-15
Next Topic: Looker Studio Cheat Sheet

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 StructureTable 2: Dimension TypesTable 3: Measure TypesTable 4: Derived TablesTable 5: Filters and ParametersTable 6: Joins and RelationshipsTable 7: Symmetric Aggregates and FanoutsTable 8: Access Control and SecurityTable 9: Value FormattingTable 10: Drill Fields and NavigationTable 11: Field OrganizationTable 12: Performance OptimizationTable 13: Aggregate AwarenessTable 14: Extending and RefinementsTable 15: SQL Runner and Ad-Hoc QueriesTable 16: Dashboard Parameters and FiltersTable 17: Looker API 4.0Table 18: EmbeddingTable 19: Actions and SchedulingTable 20: Git and Version ControlTable 21: LookML Best PracticesTable 22: Table Calculations and Custom FieldsTable 23: Looker vs Looker Studio

Table 1: LookML Project Structure

Everything in LookML nests inside a handful of building blocks, and understanding how they fit together is the foundation for the rest of this sheet. A Project holds Models, a Model points at a database connection and exposes Explores, Explores join Views together, and Views define the dimensions and measures users actually pick from — learn this hierarchy first and the rest of the language reads naturally.

ComponentExampleDescription
Project
project_name: "ecommerce"
• Collection of LookML files defining models, views, and dashboards
• stored in Git repository for version control
Model
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
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

More in Business Intelligence

  • KPI Dashboard Design Cheat Sheet
  • Looker Studio Cheat Sheet
  • Agentic Analytics and AI Copilots in BI Cheat Sheet
  • Data Storytelling Cheat Sheet
  • IBM Cognos Analytics Cheat Sheet
  • QlikView Cheat Sheet
View all 61 topics in Business Intelligence