BigQuery for Big data engineers - Master Big Query Internals | Udemy [Update 06/2025]
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A Complete deep knowledge BigQuery guide for Data engineers and Analysts. Hands-On Bigquery via Console, CLI, Python lib

What you'll learn:
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[*]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.
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**[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?_
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[*]Brief introduction to the set of services Google Cloud provides.
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[*]Complete In-depth knowledge of Google BigQuery concepts explained fromScratch to ADVANCE to Real-Time implementation.
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[*]Each and every BigQuery concept is explained with
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HANDS-ON examples
.
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[*]Includes each and every, even thin detail of Big Query.
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[*]Learn to interact with BigQuery using its Web Console, Bq CLI and Python Client Library.
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[*]Create, Load, Modify and Manage BigQuery Datasets, Tables, Views, Materialized Views etc.
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[*]*_Exclusive_
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*- 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.
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[*]Services used in the pipelines- Dataflow, Apache Beam, Pub/Sub, Bigquery, Cloud storage, Data Studio, Cloud Composer/Airflow
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etc.
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[*]Learn Best practices and Optimization techniques to follow in Real-Time Google Cloud BigQuery Projects.
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After completing this course, you can start working on any BigQuery project with full confidence.
Add-Ons
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[*]Questions and Queries will be answered very quickly.
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[*]Queries and datasets used in lectures are attached in the course for your convenience.
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[*]I am going to update it frequently, every time adding new components of Bigquery.
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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.

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