Analyzing and Visualizing Data in Looker

- Business users who need to draw insights from data

- Data analysts who are responsible for data analysis and visualization within their organizations

Upon completion of the Analyzing and Visualizing Data with Looker course, participants will be able to:

• Define Looker and the capabilities it provides for working with data
• Use dimensions, measures, and filters to analyze and visualize data
• Use dashboards for multiple visualizations and boards to curate Looker content
• Create advanced metrics by pivoting Looker data and writing table and offset calculations
• Create visualizations using Looks and dashboards
• Share Looker content with others

The Looker platform

• Define the value proposition of the Looker platform.
• Explain Looker's role in the data analysis process.
• Describe Looker's main user interface components.
• Interpret Looker's hierarchical folder structure for content.
• Discuss different content locations within the Looker platform.

Data analysis building blocks

• Define the purpose of a dimension and measure in Looker.
• Identify where end users work with dimensions, measures, and filters.
• Explain how dimensions, measures, and filters contribute to the larger data analysis process in Looker.
• Identify what asset a dimension corresponds to in your database.
• Identify what SQL functions a measure can correspond to.
• Explain how to filter by a dimension.

Working with Looker content

• Explain how to filter within a Look and a dashboard.
• Identify where users can work with dashboards and boards, and filter within Looks and dashboards.
• Explain how dashboards, boards, and filtering can contribute to the data analysis process.
• Define the purpose of a dashboard.
• Explain what a board is in Looker.
• Detail the process of creating a board.
• Detail the process for pinning Looks and dashboards to a board

Customizing Explores

• Explain the process of pivoting data.
• Identify where users can pivot data, write table calculations, and write offset calculations.
• Identify situations to consider pivoting data and writing a new table calculation.
• Explain how pivoting data, writing table calculations, and writing offset calculations can contribute to the data analysis process.
• Differentiate between a table calculation and an offset calculation.
• Discuss the various types of table calculations.
• Detail the process to write table calculations and offset calculations.

Creating new Looker content

• Explain how to create a new Look and dashboard in Looker.
• Identify where users can create new Looks and dashboards.

Sharing Looker data with others

• List the options to share Looks and dashboards once or with a regular schedule.
• Identify where users can send or schedule Looks and dashboards, and configure tile-level dashboard alerts.
• Explain how to configure a shared or scheduled Look or dashboard.
• Discuss how to choose options that are appropriate for a given situation or business case.
• Identify the options to schedule a tile-level dashboard alert.

Course Wrap-up and Resources

• PDF links to all modules

• Notions of data, tables, dashboards.
• SQL queries notions can be helpful but not mandatory

• GO9077 - Developing Data Models with LookML

• Official course book provided to participants.
• Links to Google Academy online modules provided to participants