BigQuery for Data Analysts

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

BigQuery for Data Analysts Benefits

• In this course, you will:

  • Learn the purpose and value of BigQuery, Google Cloud’s enterprise data warehouse, and discuss its data analytics features.
  • Analyze 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

BigQuery Training for Analysts Outline

Learning Objectives

Module 1) BigQuery for data analysts

• Identify analytics challenges faced by data analysts, and compare big data on-premises versus in the cloud.
• Learn the purpose and value of BigQuery, Google Cloud’s enterprise data warehouse, and discuss its data analytics features.

Module 2) Exploring and preparing your data with BigQuery

• List common data exploration techniques.
• Review SQL query basics.
• Enrich queries with functions, unions, and joins.

Module 3) Cleaning and transforming your data

• Identify what makes a good dataset.
• Clean and transform data using SQL.
• Clean and transform data with other options

Module 4) Ingesting and storing new BigQuery datasets

• Review differences between permanent and temporary data tables.
• Ingest and store new BigQuery datasets.
• Discuss options for external data sources

Module 5) Visualizing your insights from BigQuery

• Review data visualization principles and common visualization pitfalls.
• Use Connected Sheets and Looker Studio to visualize data insights from BigQuery.
• Discuss running analyses in a Jupyter Notebook

Module 6) Developing scalable data transformation pipelines in BigQuery with Dataform

• Use Dataform to develop scalable data transformation pipelines in BigQuery.
• Learn how to get started with Dataform by creating a repository and development workspace.
• Create and execute a SQL workflow in Dataform.

Module 7) BigQuery Studio

• Introduce BigQuery Studio.
• Use Duet AI in BigQuery to explain and generate SQL queries.
• Learn about new usability features and integrations with Dataform and Dataplex in the new BigQuery Studio interface.