Google BigQuery for Data Analysts (CPB 200)

- Data analysts who want to learn how to use BigQuery for their data analysis needs.

After this course participants should be able to:

• 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.
  

Module 0: Course introduction

• Introduce the topics covered in the course.

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.
• Lab: Exploring an Ecommerce Dataset using SQL in Google BigQuery
• Lab: Troubleshooting Common SQL Errors with BigQuery
• Lab: Troubleshooting and Solving Data Join Pitfalls

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.
• Lab: Creating New Permanent Tables
• Lab: Ingesting and Querying New Datasets

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.
• Lab: Connected Sheets Qwik Start
• Lab: Explore and Create Reports with Looker Studio

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.
• Demo
• Lab: 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.
• Demo
• Lab: Analyze Data with Duet AI Assistance
• Lab: Generate Personalized Email Content with BigQuery Continuous Queries and Gemini

Module 8:  Summary

• Summarize the key topics covered in the course.

• Introduction to Data Analytics on Google Cloud

None

No recommendation

Official course book provided to participants