Google BigQuery for Data Analysts

This 2-day course is designed for data analysts who want to learn about using BigQuery for their data analysis needs. Through a combination of labs and demos, this course covers various topics that discuss how to ingest, transform, and query your data in BigQuery to derive insights that can help in business decision-making.

By the end of this course, learners will be able to:

• Learn the purpose and value of BigQuery, Google Cloud’s enterprise data warehouse, and discuss its data analytics features.
• Analyse large datasets in BigQuery with SQL.
• Clean and transform your data in BigQuery with SQL.
• Ingest new BigQuery datasets and discuss options for external data sources.
• Review visualization principles, and use Connected Sheets and Looker Studio to visualize data insights from BigQuery.
• Use Dataform to develop scalable data transformation pipelines in BigQuery.
• Use new integrations and assistive capabilities introduced with BigQuery Studio.

Participants should have:

• Experience or prior learning in Data Analytics within Google Cloud

Target Audience

This course is designed for Data analysts who want to learn how to use BigQuery for their data analysis needs. This could include those in-training or currently fulfilling data analyst roles with a working knowledge of Google Cloud but have little prior experience with BigQuery before.

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

• 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.