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.
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.
