From Data to Insights with Google Cloud Platform

Price
$2,700.00 USD

Duration
3 Days

 

Delivery Methods
Virtual Instructor Led
Private Group

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Course Overview

Modern organizations are collecting more data than ever—but insight is only valuable when it’s actionable. Only 32% of available data is effectively used for business decision-making, leaving a significant opportunity for business analysts, data analysts, and cloud data engineers to lead with insight.

The From Data to Insights with Google Cloud Platform course teaches professionals how to derive insights from large-scale datasets using Google Cloud’s powerful tools. Through lectures, demos, and hands-on labs, you’ll work with BigQuery, Data Studio, Dataprep, and BigQuery ML to build complete, scalable data solutions on Google Cloud. Learn how to ingest new datasets, design efficient schemas, optimize queries, and apply machine learning—all while supporting data analysis and visualization using scalable cloud infrastructure.

Course Objectives

This course is designed to help data analysts build scalable data solutions and for engineers who will be partnering with data analysts to support data analysis pipelines and projects.

Through a combination of theory and practice, you’ll learn how to build scalable data solutions that empower stakeholders with meaningful, timely data insights. You will learn how to:

  • Perform data analysis and visualization using BigQuery and Data Studio
  • Clean and transform datasets using SQL and Google Cloud Dataprep
  • Optimize query performance and understand schema design
  • Train and deploy machine learning models using BigQuery ML
  • Apply security, access control, and best practices in analytics pipelines

Who Should Attend?

Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform
  • Top-rated instructors: Our crew of subject matter experts have an average instructor rating of 4.8 out of 5 across thousands of reviews.
  • Authorized content: We maintain more than 35 Authorized Training Partnerships with the top players in tech, ensuring your course materials contain the most relevant and up-to date information.
  • Interactive classroom participation: Our virtual training includes live lectures, demonstrations and virtual labs that allow you to participate in discussions with your instructor and fellow classmates to get real-time feedback.
  • Post Class Resources: Review your class content, catch up on any material you may have missed or perfect your new skills with access to resources after your course is complete.
  • Private Group Training: Let our world-class instructors deliver exclusive training courses just for your employees. Our private group training is designed to promote your team’s shared growth and skill development.
  • Tailored Training Solutions: Our subject matter experts can customize the class to specifically address the unique goals of your team.

What is the From Data to Insights with Google Cloud Platform course?

It’s a practical, cloud-focused course designed to help analysts derive insights from large datasets using BigQuery, Data Studio, Dataprep, and BigQuery ML.

How does this training help with scalable data work?

You’ll learn how to build pipelines, run complex queries, and structure datasets for growth—all critical for scalable data solutions on Google Cloud.

Will I learn how to work with machine learning on Google Cloud?

Yes. You’ll train models using BigQuery ML and explore pre-built ML APIs for vision, text, and forecasting—using SQL instead of code.

Who should take this course?

This course is ideal for data analysts, business analysts, and engineers who will be partnering with data analysts to support scalable analytics workflows.

Does the course include real-world practice?

Yes. You’ll complete hands-on labs and demos that simulate actual data analysis tasks using BigQuery and other Google Cloud tools.

Course Prerequisites

Basic proficiency with ANSI SQL

Agenda

Introduction to Data on Google Cloud Platform

  • Analytics challenges in the enterprise
  • Comparing cloud vs. on-premises big data solutions
  • How companies use insights with Google Cloud Platform
  • Setting up your Google Cloud project

Analyzing Large Datasets with BigQuery

  • Key features of BigQuery
  • Tools for analysts, scientists, and engineers
  • Where BigQuery fits in the analytics workflow

Exploring Your Data with SQL

  • Common data exploration strategies
  • Writing queries against public and private datasets

Cleaning and Transforming Your Data with Dataprep

  • Dataset integrity and structure
  • Using Google Cloud Dataprep for transformation
  • Applying SQL to shape and clean datasets

Visualizing Insights and Scheduling Queries

  • Principles of data visualization
  • Avoiding common design pitfalls
  • Creating dashboards with Google Data Studio
  • Scheduling recurring queries

Storing and Ingesting New Datasets

  • Temporary vs. permanent tables
  • How to ingest new datasets efficiently

Enriching Your Data Warehouse with JOINs

  • Using JOIN and UNION to merge historical datasets
  • Table wildcards and linking across schemas
  • JOIN examples and potential pitfalls

Advanced Features and Partitioning

  • Statistical and user-defined functions
  • Partitioned and clustered tables for performance
  • Advanced query structuring

Designing Schemas that Scale

  • BigQuery’s nested schema model
  • ARRAY and STRUCT syntax
  • Comparing relational and cloud-native architecture

Optimizing Queries for Performance

  • Avoiding BigQuery performance pitfalls
  • Using query plans to troubleshoot
  • Preventing data hotspots in large queries

Controlling Access with Data Security

  • Column hashing and authorized views
  • IAM roles and BigQuery access management
  • Security pitfalls in analytics environments

Predicting Return Purchases with BigQuery ML

  • Using BigQuery ML for structured prediction
  • Use case: customer lifetime value
  • Creating models with SQL

Deriving Insights from Unstructured Data

  • Business value from ML on text and images
  • Using pre-built ML APIs
  • Enhancing models with AutoML or custom training
 

Upcoming Class Dates and Times

Aug 27, 28, 29
8:00 AM - 4:00 PM
ENROLL $2,700.00 USD

Virtual: Online - CST
          

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