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.

✓ Formation officielle Google CloudNiveau Fundamentals⏱️ 1 jour (7h)

Ce que vous allez apprendre

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.

Prérequis

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

Public cible

Data analysts

Programme de la Formation

4 modules pour maîtriser les fondamentaux

Objectifs

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.

Sujets abordés

→Data analytics workflow
→Data sources
→Storage methods
→Google Cloud data analytics products
→Data types

Activités

Quiz

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.