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

Created by: J Garg - Real Time Learning
Data Engineering, Analytics and Cloud Trainer

What Will I 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.

Requirements

• Basic knowledge of SQL

Target audience

• 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.