Introduction to Data Analytics on Google Cloud

- Data analysts

After this course participants should be able to:

• Describe the data analytics workflow on Google Cloud and summarize the different types of analytics.
• Identify Google Cloud data analytics products and describe how each is used to work with data.
• Describe data sources, data structures, and data storage options in Google Cloud.
• Use BigQuery, Looker, and Looker Studio to answer data questions and influence business decisions.

Module 01 : Understand the Data Analytics Lifecycle on Google Cloud

• Detail and describe the data analytics workflow on Google Cloud.
• Compare and contrast data sources and storage methods available in Google Cloud.
• Compare how different data types can be used for data analytics.

Module 02 : Explore Data and Extract Insights by Using BigQuery

• Describe BigQuery and the BigQuery solution architecture.
• Derive insights from data by using BigQuery.
• Use the BigQuery user interface to run basic queries.
• Lab 1: BigQuery Qwik Start: Console
• Lab 2: Introduction to SQL for BigQuery and Cloud SQL
• Lab 3: BigLake: Qwik Start
• Lab 4: Analyze data with Gemini Assistance
• Quizz

Module 03 : Make Data-Driven Decisions by Using Looker

• Manipulate a Looker Explore to answer data-driven questions.
• Create a situation-appropriate visualization to highlight the answer for a datadriven question.
• Choose between Looker and Looker Studio for data visualization and sharing.
• Share visualizations with others.
• Lab 1: Looker Data Explorer—Qwik Start
• Lab 2: Looker Data Studio—Qwik Star
• Quiz

Module 4: Course Summary

• Find resources for additional learning and support.

• Basic familiarity with SQL
• Basic understanding of data concepts such as data types (relational, non-relational) and storage (data lakes, data warehouses)

None

No recommendation

• Official course book provided to participants