Data Analyst on Google Cloud

Last Updated: 08-03-2025

The Data Analyst on Google Cloud course is designed to provide aspiring data analysts and business intelligence professionals with the knowledge and skills to efficiently analyze and interpret data using Google Cloud Platform (GCP) tools and services. This course focuses on leveraging Google Cloud's powerful data analytics capabilities, including BigQuery, Google Data Studio, Cloud Dataprep, and AI and ML tools, to process, analyze, and visualize data at scale. Whether you're working with structured or unstructured data, this course will equip you with the essential skills to turn raw data into actionable insights and empower data-driven decision-making for your organization.

Schedule & Fee
Learning Objectives
Prerequisites
Target Audience
Course Modules
FAQs

July 13^th - 22^nd 09:00 AM - 05:00 PM (CST) Live Online (64 Hrs.)		10% Off $2,560 $2,304 Fast Filling! Hurry Up.
July 20^th - 10^th 06:00 PM - 10:00 PM (CST) Live Online (64 Hrs.)		10% Off $2,560 $2,304
July 25^th - 16^th 09:00 AM - 05:00 PM (CST) Live Online (64 Hrs.)		10% Off $2,560 $2,304
July 27^th - 05^th 09:00 AM - 05:00 PM (CST) Live Online (64 Hrs.) Guaranteed-to-Run		10% Off $2,560 $2,304
August 03^rd - 12^th 09:00 AM - 05:00 PM (CST) Live Online (64 Hrs.)		20% Off $2,560 $2,048
August 10^th - 19^th 09:00 AM - 05:00 PM (CST) Live Online (64 Hrs.)		20% Off $2,560 $2,048
August 17^th - 07^th 06:00 PM - 10:00 PM (CST) Live Online (64 Hrs.)		20% Off $2,560 $2,048
August 24^th - 02^nd 09:00 AM - 05:00 PM (CST) Live Online (64 Hrs.) Guaranteed-to-Run		20% Off $2,560 $2,048

Course Prerequisites

Basic understanding of data analysis concepts and techniques.
Familiarity with SQL or basic knowledge of querying databases.
No prior experience with Google Cloud is required, but familiarity with general cloud computing concepts will be helpful.
Knowledge of data visualization concepts (optional but beneficial).

Learning Objectives

By the end of the Data Analyst on Google Cloud course, you will be able to:

Understand the fundamentals of Google Cloud Platform (GCP) and its suite of data analytics tools.
Work with BigQuery, Google Cloud’s fully-managed data warehouse, to perform large-scale data analysis and create insights from structured data.
Use Google Data Studio to create interactive dashboards and share data visualizations with stakeholders.
Utilize Cloud Dataprep to clean, prepare, and transform raw data for analysis.
Work with Google Cloud Storage to store, manage, and process data efficiently in the cloud.
Perform advanced data analysis using BigQuery ML to create and deploy machine learning models directly in BigQuery.
Use Google Cloud AI tools to enhance data analysis with natural language processing, image recognition, and other AI capabilities.
Integrate Google Cloud’s machine learning services to build predictive models that support decision-making.
Leverage Cloud Functions and Cloud Pub/Sub to automate data workflows and process data in real time.
Optimize cost and performance of data analytics workloads by understanding Google Cloud’s pricing models and best practices.
Prepare for Google Cloud certifications in data analytics and data engineering, including the Professional Data Engineer certification.

Target Audience

This course is ideal for:

Aspiring data analysts looking to build a solid foundation in cloud-based data analytics.
Business intelligence professionals who want to enhance their data analysis skills using Google Cloud tools.
Data scientists who wish to learn how to leverage Google Cloud Platform for data processing and analytics.
IT professionals and developers interested in adding data analytics capabilities to their skill set.
Anyone interested in exploring careers in data analysis and gaining hands-on experience with the Google Cloud ecosystem.

Course Modules

Introduction to Cloud Data Analysis
- Defining cloud data analysis
- Roles and responsibilities of a cloud data analyst
- Overview of Google Cloud's data analytics tools: BigQuery, Cloud Storage
Data Exploration and Preparation
- Data acquisition and ingestion methods
- Cleaning and transforming data for analysis
- Using BigQuery for data exploration
Data Analysis and Visualization
- Writing SQL queries in BigQuery
- Analyzing structured and semi-structured data
- Visualizing data using Looker and Data Studio
Advanced Analytics and Machine Learning
- Introduction to machine learning models on Google Cloud
- Using AI Platform for model training and deployment
- Integrating BigQuery with machine learning tools
Data Security and Compliance
- Managing data access and permissions
- Ensuring data privacy and compliance with regulations
- Implementing security best practices in data analytics
Capstone Project
- Applying learned skills to a real-world data analysis project
- Presenting findings and insights effectively

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