BigQuery for Big data engineers – Master Big Query Internals
BigQuery for Big data engineers - Master Big Query Internals
A Complete deep knowledge BigQuery guide for Data engineers and Analysts. Hands-On Bigquery via Console, CLI, Python lib
Product Brand: Udemy
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Udemy Coupon Code for BigQuery for Big data engineers – Master Big Query Internals Course. A Complete & deep knowledge BigQuery guide for Data engineers & Analysts; Hands-On Bigquery via Console, CLI, Python lib
Created by J Garg – Real Time Learning | 9 hours on-demand video course
BigQuery for Big data engineers Course Overview
BigQuery for Big data engineers – Master Big Query Internals
[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.
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 etc.
- Learn to interact with Bigquery using Web UI, 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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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.
Taught by J Garg – Real Time Learning
