Introduction

Cloud has become a standard in many companies worldwide, even in industries where, just a few years ago, enterprise-grade on-premises solutions were dominant.

The key benefits include streamlined data analytics processes and simplified data management. One of the most significant advantages is the shift from capital expenditures (CapEx) to operational expenditures (OpEx), allowing companies to scale resources dynamically and optimize costs based on actual usage. The cloud reduces administrative overhead related to data management and infrastructure maintenance while providing quick access to cutting-edge technologies.

One of the core tools in the Google Cloud ecosystem is BigQuery—a serverless, fully-managed data warehouse optimized for high-performance analytics on massive datasets.
This time, I explored the Google Skill Boost course "Derive Insights from BigQuery Data".

Course Overview

The course provider describes it as follows:

"Complete the introductory Derive Insights from BigQuery Data skill badge to demonstrate skills in the following: write SQL queries, query public tables, load sample data into BigQuery, troubleshoot common syntax errors with the query validator in BigQuery, and create reports in Looker Studio by connecting to BigQuery data.
A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge course, and the final assessment challenge lab, to receive a skill badge that you can share with your network."

- cloudskillsboost

Technologies & Topics Covered

• BigQuery
• Data Analytics

About the Learning Platform

This course is available in the paid version of Google Cloud Skill Boost. It consists of several hands-on labs where participants complete practical tasks, with progress tracked through checkpoints.

All exercises are performed in a real Google Cloud environment—Google automatically provisions a private student account and workspace. Unlike Learning Paths, this course focuses purely on hands-on experience, with text-based instructions and practical exercises.

One aspect I find particularly useful is the time-limited access to the GCP environment. Each lab session has a predefined time frame, typically around an hour per module. This forces users to stay focused and manage their time efficiently.

What to Expect

This course provides a solid introduction to BigQuery's capabilities. Participants will familiarize themselves with the architecture of columnar databases and the specific approach required for analytical processing.

It's important to note that this is not about learning advanced SQL analytical functions but rather understanding how to work efficiently with columnar storage.
Columnar storage is optimized for analytical workloads, as it enables efficient scanning and aggregation of large datasets, unlike row-based transactional databases, which prioritize fast inserts and updates.

👉 Prior good SQL knowledge is recommended, though the introductory section provides a brief refresher.

Bonus

Upon completing the course and successfully passing the validation phase, participants earn a Google Cloud Skill Badge, which is issued via Credly.