Introduction to Data Analytics on Google Cloud

Are you completely new to data analytics and Google Cloud? This one-day course is the perfect introduction for learners with no prior experience.

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1 day course
Supporting material
Private
Private
A private training session for your team. Groups can be of any size, at a location of your choice including our training centres.

Course Credits

Select the pre-paid training investment that’s right for you and help your money stretch a little further with our course credits.

Jellyfish is an award-winning Google Cloud Partner. Our trainers work with Google Cloud on a daily basis, so you'll benefit from the years of industry experience they’ll share with you.

On this course, you'll learn the basics of data analysis, including collection, storage, exploration, visualization, and sharing. The session also introduces learners to Google Cloud’s data analytics tools and services.

Through video lectures, demos, quizzes, and hands-on labs, the course demonstrates how to go from raw data to impactful visualizations and dashboards.

This Introduction to Data Analytics on Google Cloud course is available as a private session that can be delivered virtually or at a location of your choice in the US.

Course overview

Who should attend:

This course is ideal for data analysts, as well as any other individuals interested in learning about data analytics tools and techniques on Google Cloud.

What you'll learn:

By the end of this course, you will 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

Prerequisites

In order to get the most out of this session, a basic familiarity with SQL and a basic understanding of data concepts such as data types (relational, non-relational) and storage (data lakes, data warehouses) is needed.

Course agenda

Module 1: 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 2: Explore Data & 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: BigQuery Qwik Start: Console
  • Lab: Introduction to SQL for BigQuery and Cloud SQL
  • Lab: BigLake: Qwik Start
  • Lab: Analyze data with Gemini Assistance
Module 3: 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 data-driven question
  • Choose between Looker and Looker Studio for data visualization and sharing
  • Share visualizations with others
  • Lab: Looker Data Explorer - Qwik Start
  • Lab: Looker Data Studio - Qwik Start
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