BigQuery for Data Analysts

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) Visualising your insights from BigQuery

• Review data visualisation principles and common visualisation pitfalls.
• Use Connected Sheets and Looker Studio to visualise 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.