Detailed Course Outline
Module 1 - Understand the Data Analytics Lifecycle on Google Cloud
Topics:
- Data analytics workflow
- Data sources
- Storage methods
- Google Cloud data analytics products
- Data types
Objectives:
- Detail and describe the data analytics workflow on Google Cloud.
- Compare and contrast data sources and storage methods available in Google Cloud.
- Compare how different data types can be used for data analytics.
Activities:
- Quiz
Module 2 - Explore Data and Extract Insights by Using BigQuery
Topics:
- BigQuery services, capabilities, and organization
- Data storage
- Basic SQL
- Answering data-driven questions
Objectives:
- Describe BigQuery and the BigQuery solution architecture.
- Derive insights from data by using BigQuery.
- Use the BigQuery user interface to run basic queries
Activities:
- Lab 1: BigQuery Qwik Start: Console
- Lab 2: Introduction to SQL for BigQuery and Cloud SQL
- Lab 3: BigLake: Qwik Start
- Lab 4: Analyze data with Gemini Assistance
- Quiz
Module 3 - Make Data-Driven Decisions by Using Looker
Topics:
- Looker data exploration terms and concepts
- Looks and dashboards
- Visualizations
- Report sharing
- Looker Studio
Objectives:
- Manipulate a Looker Explore to answer data-driven questions.
- Create a situation-appropriate visualization to highlight the answer for a datadriven question.
- Choose between Looker and Looker Studio for data visualization and sharing.
- Share visualizations with others.
Activities:
- Lab 1: Looker Data Explorer—Qwik Start
- Lab 2: Looker Data Studio—Qwik Start
- Quiz
Module 4 - Course Summary
Topics:
- Topic review
- Slides
Objectives:
- Find resources for additional learning and support.