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Course Outline
Introduction to Looker Studio
- Cloud-native reporting architecture and navigating the interface.
- Building your initial report: distinguishing between reports, dashboards, and pages.
- Configuring defaults, managing themes, and adhering to organizational branding guidelines.
- Lab 1: Setting up a Looker Studio environment, creating a blank report, and applying a custom theme.
Managing Data Sources
- Overview of connector types and supported platforms (Google Sheets, CSV, BigQuery, GA4, MySQL, etc.).
- Configuring connections, setting refresh intervals, and understanding query limits.
- Data validation techniques: schema inspection, field type mapping, and troubleshooting errors.
- Lab 2: Linking two data sources, verifying data ingestion, and scheduling automated refreshes.
Metrics and Dimensions
- Grasping field types: metrics (aggregations) versus dimensions (categorical/text data).
- Setting up breakdowns, date ranges, and rollups for context-rich reporting.
- Handling null values, missing data, and standardizing timezone/date formats.
- Lab 3: Constructing base tables and charts using raw dimensions/metrics with dynamic date controls.
Filters and Sorting
- Distinguishing between report-level, page-level, and chart-level filters.
- Implementing date range controls, dropdowns, checkboxes, and search filters.
- Sorting mechanisms: alphabetical, numeric, reverse order, and multi-field sorting.
- Lab 4: Adding interactive filters to a dashboard, testing filter dependencies, and optimizing query performance.
Data Calculations
- Developing custom metrics and dimensions within Looker Studio.
- Utilizing formula functions:
CASE,REGEXP,DATE_DIFF,IF,SUM,AVG, and string manipulation. - Performance implications: choosing between computed fields and source-level calculations.
- Lab 5: Writing custom KPIs, conditional formatting logic, and derived metrics using native functions.
Creating Visualizations and Dashboard Design
- Choosing the right chart types for specific business questions (tables, bar/line charts, scorecards, geo maps, scatter plots, pivot tables).
- Enhancing interactivity: click-through URLs, drill-down capabilities, and tooltip customization.
- Layout and responsive design: utilizing grid systems, padding, alignment, and optimizing for mobile/tablet views.
- Accessibility and readability: ensuring proper contrast, clear labeling, and effective data storytelling.
- Lab 6: Constructing a multi-page dashboard with a responsive layout, interactive elements, and professional styling.
Data Blending
- Understanding join types: inner, left/right outer, and full outer joins in Looker Studio.
- Defining common dimensions and addressing mismatched data keys.
- Blending strategies: pre-aggregation, normalization, and performance tuning.
- Lab 7: Blending two datasets (e.g., sales data combined with marketing spend), validating join results, and resolving common blending errors.
Sharing and Publishing
- Managing access controls: viewers, commenters, editors, and organization-specific permissions.
- Configuring auto-refresh, email subscriptions, and scheduled report distribution.
- Embedding reports into websites/portals and utilizing export options (PDF, CSV, PPTX).
- Dashboard governance: versioning, naming conventions, and maintaining audit trails.
- Lab 8: Publishing a production-ready dashboard, setting sharing permissions, configuring auto-refresh, and exporting artifacts.
Capstone Project & Real-World Implementation
- Completing an end-to-end workflow: data connection → calculations → filters → visualization → publishing.
- Peer review of dashboard projects with facilitator feedback on design, performance, and clarity.
- Open Q&A session, troubleshooting common connector/calculation errors, and distributing resources.
- Deliverable: Participants submit a fully functional, interactive Looker Studio dashboard along with supporting documentation.
Requirements
- A Gmail account
- Fundamental familiarity with spreadsheets, data structures, or reporting workflows (not mandatory)
7 Hours
Testimonials (2)
The final day which is the Machine Learning Topic
John Erick Baltazar - Globe Telecom
Course - Google BigQuery
It was a really good training course, well prepared and explained by the trainer with great hands on experience on GCP.
