MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 93 lectures (7h 46m) | Size: 1.46 GB
Learn Full In & Out of Google Cloud BigQuery with proper HANDS-ON examples from scratch.
A Complete & deep knowledge BigQuery guide for Data eeers & Analysts; Hands-On Bigquery via UI, CLI, Python library
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 etc.
Learn to interact with Bigquery using Web UI, Command Line, Python Client Library etc.
Learn Best practices to follow in Real- 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.
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 Big query concepts/Internals.
**Coming Soon** - Advance BigQuery GIS functions, 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- 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- case study in GCP.
Services used in the pipeline- Dataflow, Apache Beam, BigQuery, Cloud storage, Data Studio, Cloud Composer etc.
Learn Best practices and Optimization techniques to follow in Real- Google Cloud BigQuery Projects.
After completing this course, you can start working on any BigQuery project with full confidence.
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 adding new components of Big Query.
Students who want to learn Deep Internals of BigQuery components
Data eeers, intending to build end-to-end Data pipelines in GCP (Google Cloud Platform)
Anyone planning to give Google Cloud Data eeer certification.
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