BigQuery for Big data engineers – Master Big Query Internals

A Complete & deep knowledge BigQuery guide for Data engineers & Analysts; Hands-On Bigquery via UI, CLI, Python library

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.

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, 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..

Course Content

  • Introduction to GCP & its services –> 7 lectures • 37min.
  • Introduction to BigQuery –> 4 lectures • 17min.
  • Dataset & Table creation –> 6 lectures • 26min.
  • Using BigQuery Dashboard options –> 6 lectures • 38min.
  • Efficient Schema Design in BigQuery –> 2 lectures • 11min.
  • Operations on Datasets & Tables –> 4 lectures • 24min.
  • Execution Plan of BigQuery –> 2 lectures • 14min.
  • Partitioned Tables in BigQuery –> 7 lectures • 43min.
  • Clustered Tables in BigQuery –> 4 lectures • 16min.
  • Loading & Querying External Data Sources –> 3 lectures • 14min.

BigQuery for Big data engineers - Master Big Query Internals

Requirements

  • Basic knowledge of SQL.

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.

**Coming Soon** –  Streaming Pipeline in GCP

“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 UI dashboard, 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 an end-to-end data pipeline of a Real-Time case study in GCP.
  • Services used in the pipeline- Dataflow, Apache Beam, 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.
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