BigQuery for Big data engineers - Master Big Query Internals

Name: BigQuery for Big data engineers - Master Big Query Internals
Rating: 4.4 (4221 reviews)

A Complete deep knowledge BigQuery guide for Data engineers and Analysts. Hands-On Bigquery via Console, CLI, Python lib

Bestseller

Created byJ Garg - Real Time Learning

Last updated 6/2025

English

What you'll learn

Learn Full In & Out of Google Cloud BigQuery with proper HANDS-ON examples from scratch.
Get an Overview of Google Cloud Platform and a brief introduction to the set of services it provides.
Start with Bigquery core concepts like understanding its Architecture, Dataset, Table, View, Materialized View, Schedule queries, Limitations & Quotas.
ADVANCE Big query topics like Query Execution plan, Efficient schema design, Optimization techniques, Partitioning, Clustering, etc.
Build Big data pipelines using various Google Cloud Platform services - Dataflow, Pub/Sub, BigQuery, Cloud storage, Beam, Data Studio, Cloud Composer/Airflow.
Learn to interact with Bigquery using Web Console, Command Line, Python Client Library etc.
Learn Best practices to follow in Real-Time Projects for Performance and Cost saving for every component of Big query.
Bigquery Pricing models for Storage, Querying, API requests, DMLs and free operations.
Data-sets and Queries used in lectures are available in resources tab. This will save your typing efforts.

Course content

20 sections • 105 lectures • 8h 47m total length

Introduction to Google Cloud Platform2:13
What is google cloud platform - An introduction to GCP
GCP vs AWS vs Azure - Why choose GCP6:03
Comparison between major Cloud providers - (Google cloud Platform) GCP , AWS and Azure. Why choose GCP
Compute Services in GCP5:35
In this lecture you will learn what all Compute services Google cloud platform (GCP) provides
Storage Services in GCP5:32
In this lecture you will learn what all Storage services Google cloud platform (GCP) provides
Big data Services in GCP3:56
In this lecture you will learn what all Big data services Google cloud platform (GCP) provides
AI & ML Services in GCP8:27
In this lecture you will learn what all Artificial Intelligence and Machine learning services Google cloud platform (GCP) provides
Big data ecosystem in GCP4:47
This lecture explains what all Google cloud platform (GCP) services are responsible to generate Big data pipelines for both batch and streaming data.
Quiz 1

Conventional Datawarehouse Problems3:41
How does datawarehouse evolved over the time? What are the problems faced by conventional datawarehouses
What is BigQuery3:38
Introduction to Google cloud Big query
BigQuery Out-of-the Box Features4:01
In this lecture, you will learn various features of Bigquery
Architecture of BigQuery5:43
You will learn How BigQuery architecture is . Storage and compute are separated.

Setup a GCP account0:45
Important note0:14
Create a Project4:35
Create first project in Google cloud Bigquery
BigQuery UI Tour12:57
This lecture will give you a very first look of What all options are present in Google cloud Bigquery's dashboard.
Create a Dataset - Part 13:23
Region Vs Multi-region4:16
What are the difference between storing data in region and multi-region in Google cloud
Create a Dataset - Part 27:17
Create first Dataset in Google cloud Bigquery
Create a Table8:11
Create first Table in Google cloud Bigquery
Assignment 1

Running query with various Query Settings5:18
Run 1st SQL query in Big query's UI dashboard
Caching features & limitations3:41
Query results can be cached in Big query. This lecture shows what are some of the features and limitations of caching a query results in google cloud BigQuery
Querying Wildcard Tables8:10
What are wildcard tables and How to query wildcard tables in Big query
Wildcard Table Limitations4:01
What all are the limitations of querying a Wildcard table in BigQuery
Schedule, Save, Share a Query9:16
Schedule, save and share a query from bigquery's UI dashboard.
Schema Auto detection5:14
Learn How Big query Auto detects the schema from a file and what are its limitations.

Copying Datasets5:05
Copy a data set from any combination of regions and multi-regions in Bigquery
Transfer Service for scheduling Copy Jobs4:03
Use Google cloud Transfer service to schedule your copy jobs of Bigquery
Modifying Table Schema - Part 17:04
This video will tell you what all schema changes are natively allowed by Big query.
Modifying Table Schema - Part 29:10
Modifying table schema part 2
Restore Deleted data from Table4:09

What is Partitioning & its benefits5:01
In this lecture, we will discuss partitioning in general and its benefits.
Ingestion time Partitioned Tables9:22
What are ingestion time partitioned tables and How to create ingestion time partitioned tables in Bigquery
Date column Partitioned Tables6:49
What are date partitioned tables and How to create date partitioned tables in Bigquery
Integer based Partitioned Tables5:05
What are integer column partitioned tables and How to create integer column partitioned tables in Bigquery
ALTER, COPY operations on Partitioned Tables5:25
Perfom DML operations on bigquery Partitioned tables
DML operations on Partitioned Tables4:17
DML operations on Bigquery partitioned tables.
Best Practices for Partitioning7:27
Dos and Don'ts + Best practices to be followed in partitioned tables of Big query

Requirements

Basic knowledge of SQL

Description

**[Updated 2024]** - This course is updated as per latest BigQuery UI and features.

Note : This Bigquery course is NOT intended to teach SQL or PostgreSQL. The focus of the course is kept to give you In-depth knowledge of Google Bigquery concepts/Internals.

"BigQuery is server-less, highly scalable, and cost-effective Data warehouse designed for Google cloud Platform (GCP) to store and query petabytes of data."

What's included in the course ?

Brief introduction to the set of services Google Cloud provides.
Complete In-depth knowledge of Google BigQuery concepts explained from Scratch to ADVANCE to Real-Time implementation.
Each and every BigQuery concept is explained with HANDS-ON examples.
Includes each and every, even thin detail of Big Query.
Learn to interact with BigQuery using its Web Console, Bq CLI and Python Client Library.
Create, Load, Modify and Manage BigQuery Datasets, Tables, Views, Materialized Views etc.
*Exclusive* - Query Execution Plan, Efficient schema design, Optimization techniques, Partitioning, Clustering.
Build and deploy end-to-end data pipelines (Batch & Stream) of Real-Time case studies in GCP.
Services used in the pipelines- Dataflow, Apache Beam, Pub/Sub, Bigquery, Cloud storage, Data Studio, Cloud Composer/Airflow etc.
Learn Best practices and Optimization techniques to follow in Real-Time Google Cloud BigQuery Projects.

After completing this course, you can start working on any BigQuery project with full confidence.

Add-Ons

Questions and Queries will be answered very quickly.
Queries and datasets used in lectures are attached in the course for your convenience.
I am going to update it frequently, every time adding new components of Bigquery.

Who this course is for:

Students who want to learn Deep Internals of BigQuery components.
Data engineers, intending to build end-to-end Data pipelines in GCP (Google Cloud Platform)
Anyone planning to give Google Cloud Data engineer certification.

BigQuery for Big data engineers - Master Big Query Internals

What you'll learn

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Course content

Introduction to GCP & its services7 lectures • 37min

Introduction to BigQuery4 lectures • 17min

Dataset & Table creation8 lectures • 42min

Using BigQuery Dashboard options6 lectures • 36min

Efficient Schema Design in BigQuery2 lectures • 11min

Operations on Datasets & Tables5 lectures • 30min

Execution Plan of BigQuery2 lectures • 14min

Partitioned Tables in BigQuery7 lectures • 43min

Clustered Tables in BigQuery4 lectures • 16min

Loading & Querying External Data Sources3 lectures • 14min

Requirements

Description

Who this course is for: