Build a No-Code ETL Pipeline with Google BigQuery

2h 42mIntermediate2025-01-27

Authors

Vlad Gheorghe

Course details

Learn to build a no-code data pipeline using BigQuery in this hands-on course. Get started with data ingestion, write SQL to process your data, and finish by creating a live dashboard. Perfect for beginners, this course enables you to gain practical skills in ETL processes, data visualization, and working with cloud-based tools. When you complete this course, you will have created a real project that updates automatically, using free resources in the BigQuery ecosystem.

Learning objectives
Define how BigQuery works and how you can leverage it for data analytics.
Identify how to use BigQuery Data Transfer Service to load your data in BigQuery.
Determine how to transform your data with SQL in BigQuery, with an eye to efficiency and cost control.
Articulate how to use BigQuery Scheduler to automate your queries and get alerted in case of issues.
Examine how to build live dashboards for your data in Looker Studio.

Skills covered

BigQueryData EngineeringGenerative AIGoogleCloud ServicesData AnalysisCloud PlatformsArtificial Intelligence (AI)Cloud ComputingData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOne-Off

Concepts

0. Introduction

01 - Introduction
02 - What you will learn

1. Data Pipelines in BigQuery

03 - Introduction to ETL and ELT pipelines
04 - How data is organized in SQL
05 - What is Google Cloud
06 - What is BigQuery
07 - Real-world project in BigQuery
08 - How to control costs in Google Cloud

2. Ingest Data into BigQuery

09 - How data load will work
10 - Introduction to data
11 - What is Google Cloud Storage
12 - Put data in Google Cloud Storage
13 - Create table in BigQuery
14 - Introduction to BigQuery Data Transfer Service
15 - How we will manage data
16 - Use Transfer Service to ingest data
17 - Schedule transfers with Transfer Service
18 - Identify data transfer issues
19 - Common issues with data transfer

3. Process Data in BigQuery

20 - The BigQuery interface
21 - Create and modify tables in BigQuery
22 - Understand BigQuery pricing
23 - Create analytics table
24 - Process data, part one
25 - Process data, part two
26 - Schedule query and manage issues

4. Build a Dashboard in Looker Studio

27 - Introduction to Looker Studio
28 - Create a data source
29 - Create a basic dashboard
30 - Explore Looker Studio features
31 - Calculated fields
32 - Time series
33 - Share and schedule dashboard

5. Conclusion

34 - Clean up resources
35 - Next steps