GCP100DA

Introduction to Data Analytics on Google Cloud

This course is an introduction to data analytics on Google Cloud. It is designed for learners who have no prior experience with data analytics or Google Cloud. The course covers the basics of data analysis, including collection, storage, exploration, visualization, and sharing. It 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.

Google Cloud
✓ Official training Google CloudLevel Fundamentals⏱️ 1 day (7h)

What you will learn

  • 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

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

Target audience

  • Data analysts

Training Program

4 modules to master the fundamentals

Objectives
  • 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.
Topics covered
  • →Data analytics workflow
  • →Data sources
  • →Storage methods
  • →Google Cloud data analytics products
  • →Data types
Activities

Quiz

Objectives
  • Describe BigQuery and the BigQuery solution architecture.
  • Derive insights from data by using BigQuery.
  • Use the BigQuery user interface to run basic queries.
Topics covered
  • →BigQuery services, capabilities, and organization
  • →Data storage
  • →Basic SQL
  • →Answering data-driven questions
Activities

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

Quiz

Objectives
  • 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.
Topics covered
  • →Looker data exploration terms and concepts
  • →Looks and dashboards
  • →Visualizations
  • →Report sharing
  • →Looker Studio
Activities

Lab 1: Looker Data Explorer—Qwik Start

Lab 2: Looker Data Studio—Qwik Start

Quiz

Objectives
  • Find resources for additional learning and support.
Topics covered
  • →Topic review
  • →Slides

Related Trainings

SFEIR Institute
Best

dbt

Learn to transform your data with dbt, the leading tool in the Modern Data Stack. You'll start by understanding the evolution of data architectures and the difference between ETL and ELT. You'll install dbt, create your first project and connect it to your data sources. Then you'll learn to build structured data models, choose the right materialization options (table, view, incremental) and organize your metadata with tags. You'll discover how to reference your sources and manage dependencies between models. You'll explore advanced features: seeds to initialize reference data, snapshots to track history and manage slowly changing dimensions, Jinja macros and variables to automate your transformations. Finally, you'll implement automated tests to ensure data quality, document your models with lineage, and discover packages from the dbt community. Hands-on training with 60% labs.

2 d
Fundamental
Google Cloud

Analyzing and Visualizing Data in Looker

In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. You learn to leverage Looker's modern analytics platform to find and explore relevant content in your organization's Looker instance. You also discover how to ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision-making.

1 d
Fundamental

Upcoming sessions

March 13, 2026
Distanciel • Français
Register
April 15, 2026
Distanciel • Français
Register
May 7, 2026
Distanciel • Français
Register
June 3, 2026
Distanciel • Français
Register
July 7, 2026
Distanciel • Français
Register
August 19, 2026
Distanciel • Français
Register
September 11, 2026
Distanciel • Français
Register
October 19, 2026
Distanciel • Français
Register
November 13, 2026
Distanciel • Français
Register
December 16, 2026
Distanciel • Français
Register

Quality Process

SFEIR Institute's commitment: an excellence approach to ensure the quality and success of all our training programs. Learn more about our quality approach

Teaching Methods Used
  • Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
  • Technical Demonstration (Demos) — The instructor performs a task or procedure while students observe.
  • Guided Labs — Guided practical exercises on software, hardware, or technical environments.
  • Quiz / MCQ — Quick knowledge check (paper-based or digital via tools like Kahoot/Klaxoon).
Evaluation and Monitoring System

The achievement of training objectives is evaluated at multiple levels to ensure quality:

  • Continuous Knowledge Assessment : Verification of knowledge throughout the training via participatory methods (quizzes, practical exercises, case studies) under instructor supervision.
  • Progress Measurement : Comparative self-assessment system including an initial diagnostic to determine the starting level, followed by a final evaluation to validate skills development.
  • Quality Evaluation : End-of-session satisfaction questionnaire to measure the relevance and effectiveness of the training as perceived by participants.

790€ excl. VAT

per learner