Course
digicode: LOOKAV
Analyzing and Visualizing Data in Looker
Learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts.
Duration
1 day
Price
850.–
exkl. 8.1% MWST
Course documents
Official Google Cloud courseware
Course facts
- Defining Looker and the capabilities it provides for working with data
- Using dimensions, measures, and filters to analyze and visualize data
- Using dashboards for multiple visualizations and boards to curate Looker content
- Creating advanced metrics by pivoting Looker data and writing table and offset calculations
- Creating visualizations using Looks and dashboards, and sharing Looker content with others
You learn to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance. You also discover how to ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision-making.
1 The Looker Platform
- What is Looker?
- Looker user interface
- Organizing content with folders
- 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
2 Data Analysis Building Blocks
- Dimensions in Looker
- Measures in Looker
- Using dimensions and measures
- Filtering dimensions
- Filtering measures
- 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
3 Working with Looker Content
- Filtering Looks
- Introducing dashboards
- Filtering dashboards
- Curating Looker content in boards
- 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
4 Customizing Explores
- Pivoting data in Looker
- Introduction to table calculations
- Types of table calculations
- Writing table calculations
- Introducing offset functions
- Writing offset calculations
- 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
5 Creating New Looker Content
- Creating new Looks
- Creating new dashboards
- Explain how to create a new Look and dashboard in Looker.
- Identify where users can create new Looks and dashboards.
6 Sharing Looker Data with Others
- Sharing and scheduling Looks
- Sharing and scheduling dashboards
- Tile-level dashboard alerts
- 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.
- Business users who need to draw insights from data
- Data analysts who are responsible for data analysis and visualization within their organizations
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