Data Engineering with Google BigQuery & Google Cloud
Learn Google BigQuery, Google Cloud, data pipelines, SQL, warehousing, analytics and transformation skills through structured data engineering training.
321 Students
Overview
Data Engineering with Google BigQuery and Google Cloud introduces learners to modern cloud-based data engineering using BigQuery and Google Cloud technologies. This Google BigQuery data engineering course covers data warehouses, querying, data types, data quality, transformation, storage, and visualisation. Furthermore, learners explore Google Cloud data engineering, BigQuery for beginners, and data engineering with GCP through structured modules. The curriculum also covers cloud data engineering course concepts, Google Cloud Platform training, BigQuery data warehouse workflows, cloud data analytics, data pipeline development, and Google Cloud data engineering training.
Course Description
Turn raw information into useful business intelligence with Data Engineering with Google BigQuery and Google Cloud. This Google BigQuery data engineering course introduces learners to data warehousing, BigQuery’s interface, SQL queries, functions, and common data types. First, the programme establishes Google Cloud data engineering foundations while making BigQuery for beginners easier to approach. Learners then explore queries, data conversion and essential warehouse concepts. Consequently, the cloud data engineering course provides a structured route into modern data platforms.
Next, the curriculum focuses on data quality, cleaning, transformation and storage. Through data engineering with GCP, learners explore scheduled queries, DataPrep, data analysis and visualisation. Moreover, Google Cloud Platform training introduces workflows for loading information efficiently, handling errors and working with recurring data. The programme also examines BigQuery data warehouse concepts and connects them with cloud data analytics, enabling learners to work with information from different sources.
Finally, learners explore BigQuery views, Google Sheets, Google Data Studio, joins, unions, intersections and statistical functions. These topics support data pipeline development and provide context for broader Google Cloud data engineering training. Therefore, this Google BigQuery data engineering course offers a comprehensive foundation for learners progressing towards cloud-focused data roles and more advanced Google Cloud data engineering responsibilities.
Learning Outcomes
- Explore Google BigQuery data engineering course concepts and core warehouse workflows.
- Work with BigQuery for beginners topics, queries, functions, and data types.
- Apply data engineering with GCP methods for cleaning, transforming, and storing information.
- Explore cloud data analytics through analysis, visualisation and BigQuery views.
- Develop foundations for data pipeline development and Google Cloud data engineering training.
Who Is This Course For?
- Beginners seeking Google Cloud Platform training and an accessible introduction to BigQuery.
- Aspiring data professionals interested in Google Cloud data engineering and cloud technologies.
- Learners exploring a cloud data engineering course focused on warehouse and pipeline concepts.
- Analysts interested in BigQuery data warehouse workflows and cloud data analytics.
- Developers preparing for data engineering with GCP and Google Cloud data engineering training.
Certification
Once the Data engineering with Google BigQuery and Google Cloud is successfully completed, the learner can obtain the PDF certificate without any cost. The hard copy of the certificate is also available for £4.99. However, anyone ordering the hard copy certificate from outside the United Kingdom may incur an additional delivery charge.
Career Path
Data Engineer
Designs and maintains systems that collect, transform, organise and deliver data for analytical and operational use.
Average Salary: £50,000 – £75,000 per year
Cloud Data Engineer
Builds cloud-based data solutions, storage environments and processing workflows using platforms such as Google Cloud.
Average Salary: £55,000 – £80,000 per year
BigQuery Data Engineer
Works with BigQuery environments to manage datasets, queries, transformations and warehouse-oriented solutions.
Average Salary: £50,000 – £75,000 per year
Data Analyst
Examines datasets, identifies trends and produces reports or visual outputs that support organisational decisions.
Average Salary: £40,000 – £60,000 per year
Business Intelligence Developer
Creates analytical solutions, dashboards and reporting systems that transform organisational data into useful insights.
Average Salary: £45,000 – £70,000 per year
Cloud Solutions Architect
Plans scalable cloud architectures and advises organisations on technology structures, data platforms and digital solutions.
Average Salary: £65,000 – £90,000 per year
Schema Markup
Frequently Asked Questions (FAQs)
A Google BigQuery data engineering course introduces data warehousing, querying, transformation, loading and analytical workflows using BigQuery and Google Cloud technologies.
Yes. BigQuery for beginners provides an accessible starting point for learners who want to explore cloud-based data storage, SQL querying and analytics.
Google Cloud data engineering involves designing, processing, transforming and managing data using Google Cloud services and related technologies.
Yes. This cloud data engineering course covers warehouse concepts, data loading, transformation, scheduled queries, analysis and visualisation.
Data engineering with GCP refers to building and managing data workflows using Google Cloud Platform services, including BigQuery and associated tools.
Data Engineering with Google BigQuery & Google Cloud Course Reviews
An outstanding online course with clear explanations and practical examples. I could study at my own pace and still feel fully supported throughout. It’s truly boosted my confidence and career prospects
The course was well-structured, engaging, and easy to follow. The flexibility made it perfect alongside my full-time job. I’ve gained valuable, real-world skills that I can apply immediately.
Excellent learning experience from start to finish. The content was professional, up-to-date, and highly relevant. I would highly recommend it to anyone looking to upskill online.
Course Curriculum
| Unit 01: Introduction | |||
| Module 01: Welcome to This Course | 00:01:00 | ||
| Module 02: How to Get Maximum Value from This Course | 00:06:00 | ||
| Module 03: Course Structure & Coverage | 00:02:00 | ||
| Module 04: Technology in This Course | 00:02:00 | ||
| Unit 02: Introducing Data Warehouse & BigQuery | |||
| Module 01: Data Warehouse | 00:07:00 | ||
| Module 02: Start With BigQuery | 00:05:00 | ||
| Module 03: BigQuery Web User Interface | 00:04:00 | ||
| Unit 03: First Exploration | |||
| Module 01: First Data | 00:04:00 | ||
| Module 02: Basic Exploration | 00:16:00 | ||
| Module 03: Functions | 00:14:00 | ||
| Module 04: Common Data Types | 00:07:00 | ||
| Module 05: Different Query | 00:01:00 | ||
| Module 06: Exploring Common Data Types | 00:25:00 | ||
| Module 07: Converting Data Types | 00:07:00 | ||
| Unit 04: Data Flow Basic | |||
| Module 01: Data Quality | 00:06:00 | ||
| Module 02: Clean & Transform | 00:13:00 | ||
| Module 03: Store Data | 00:06:00 | ||
| Module 04: Upgrading From Sandbox Account | 00:01:00 | ||
| Module 05: Clean & Transform With Dataprep | 00:25:00 | ||
| Module 06: Scheduled Query | 00:04:00 | ||
| Module 07: Analyze Data | 00:05:00 | ||
| Module 08: Data Visualization | 00:06:00 | ||
| Unit 05: Diving into BigQuery | |||
| Module 01: Essential BigQuery | 00:15:00 | ||
| Module 02: Load Data into BigQuery (Part 1) – The Basic | 00:36:00 | ||
| Module 03: Tip: Mock Data | 00:01:00 | ||
| Module 04: Load Data into BigQuery (Part 2) – Handling Errors | 00:22:00 | ||
| Module 05: Load Data into BigQuery (Part 3) – Efficient Load | 00:14:00 | ||
| Module 06: Load Data into BigQuery (Part 4) – From Your Data to BigQuery | 00:23:00 | ||
| Module 07: Load Data into BigQuery (Part 5) – In Microservice Architecture | 00:20:00 | ||
| Module 08: Tip: Message Broker Overview | 00:08:00 | ||
| Module 09: Load Data into BigQuery (Part 6) – Recurring Load | 00:12:00 | ||
| Unit 06: Virtual Data using View | |||
| Module 01: BigQuery View | 00:06:00 | ||
| Unit 07: Data Visualization | |||
| Module 01: What We Will Learn | 00:01:00 | ||
| Module 02: Google Sheets & BigQuery | 00:10:00 | ||
| Module 03: Google Data Studio | 00:13:00 | ||
| Unit 08: Intermediate Query | |||
| Module 01: Using Join – Theory | 00:04:00 | ||
| Module 02: Using Join – Hands On | 00:16:00 | ||
| Module 03: Union & Intersect | 00:06:00 | ||
| Module 04: Basic Statistical Functions | 00:05:00 | ||
| Assignment | |||
| Assignment – Data Engineering with Google BigQuery & Google Cloud | 2 weeks, 4 days | ||
| Order Your Certificate | |||
| Order Your Certificate QLS | 00:00:00 | ||
Frequently Asked Questions
Yes, Discover Training provides accredited and CPD-certified courses, ensuring learners receive recognised qualifications that support career progression and professional compliance.
Anyone can enrol, including students, professionals, job seekers, career changers, and organisations. Most courses do not require previous experience, making them accessible to learners at all levels.
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You will have 14 days to revoke your Course purchase from your purchase date. Regrettably, refunds are not allowed after your purchase have been approved, and materials have been posted to the student’s dashboard or accessed.
Yes, learners receive a downloadable digital certificate upon successful completion, suitable for CPD records, CVs, and professional portfolios.
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Number of Units:
41 -
Access:
1 Year -
Duration:
2 weeks, 5 days -
PDF Certificate
Included
