Module 0: Course Introduction
- This module introduces the course agenda
Module 1: BigQuery for Data Analysts
- Overview
- Data analytics on Google Cloud
- From data to insights with BigQuery
- Real-world use cases of companies transformed through analytics on Google Cloud
Module 2: Exploring and preparing your data with BigQuery
- Overview
- Common data exploration techniques
- Analysis of large datasets with BigQuery
- Query basics
- Working with functions
- Enriching your queries with UNIONs and JOINs
Module 3: Cleaning and transforming your data
- Overview
- Five principles of dataset integrity
- Clean and transform data using SQL
- Clean and transform data: Other options
Module 4: Ingesting and storing BigQuery datasets
- Overview
- Permanent versus temporary data tables
- Ingesting new datasets
- External data sources
Module 5: Visualising your insights from BigQuery
- Overview
- Data visualization principles
- Connected Sheets
- Common data visualization pitfalls
- Looker Studio
- Analysis in a notebook
Module 6: Developing scalable data transformation pipelines in BigQuery with
Dataform
- Overview
- What is Dataform?
- Getting started with Dataform
Module 7: BigQuery Studio
- BigQuery Studio: What and why?
- Unified analytics
- Asset management
- Embedded assistance
Module 8: Summary
Exams and Assessments
There are no formal examinations within this course. There will be a module review and summary following the practical hands-on lab, quiz and slide-deck deliveries. This will further enforce learning and support additional resource finds, for continued learning and development.
Hands-on Learning
Within this course there are opportunities for learners to engage in hands-on labs to support module learning. In addition, each module will also have a quiz, to support knowledge capture.