Pivot a dimension

Reorder columns and remove fields

Use table calculations and Use Looker functions

Create a new visualization from the Explore and save to a new dashboard

Prepare the dashboard for one-time distribution

Schedule the dashboard for regular distribution

Use the Explore interface to create a visualization.

Save a visualization to a new dashboard.

Create a tile-based dashboard alert.

Modify a time-based dashboard alert.

Define LookML basic terms and building blocks

Model new dimensions and measures using LookML and use dashboards to combine key queries and visualizations into a one page executive view

Model files of LookML projects to design and build custom Explores for business users

Use derived tables in Looker to create new custom tables and use datagroups to manage caching policies

Define and read LookML

Organize and understand the main LookML structures and create a view

Add dimensions and measures to the view

Join a view to an existing Explore

Learn how caching works in Looker

Explore how to use LookML datagroups to define caching policies

Create native derived tables to answer complex questions using derived columns

Update a native derived table to generate dynamic values using built-in filter parameters

Understand how business users leverage customized native derived tables to answer complex questions

Create SQL derived tables to address multiple use cases

Update a SQL derived table to generate dynamic values using templated filters with Liquid

Understand how business users leverage dynamic SQL derived tables to answer complex questions

Understand the different use cases for each filter

Use the sql_always_where and sql_always_having filters

Use the always_filter

Use the conditionally_filter

Use SQL Runner to explore data tables and troubleshoot SQL queries.

Use the LookML Validator to validate syntax for defined objects and relationships.

Diagnose and resolve error messages from Explore queries.

Diagnose and resolve error messages from running the Content Validator.

Use descriptive field names to define dimensions and measures.

Leverage additional parameters to organize and provide more context for your data.

Create and surface the fewest number of fields and Explores possible.

Write sustainable and modular LookML code that can easily be updated, maintained, and reused.