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Creating an ETL Data Pipeline on Google Cloud with Cloud Data Fusion & Airflow - Part 1

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Python Faker

Cloud Fusion

Data Fusion

GCS

Data Transformation

Data Visualization

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Автор: TechTrapture

Загружено: 2024-02-23

Просмотров: 83251

Описание: Part 2 -    • Creating an ETL Data Pipeline on Google Cl...  
Source Code - https://github.com/vishal-bulbule/etl...

Creating an ETL Data Pipeline on Google Cloud with Cloud Data Fusion & Airflow
Explore the magic of building an ETL pipeline in Google Cloud with this comprehensive tutorial. Learn how to craft a seamless process for extracting, transforming, and loading data into BigQuery, then visualize it effortlessly in Looker Studio.

Step 1: Begin by extracting dummy employee data using the Python Faker library, seamlessly storing it in a designated Google Cloud Storage (GCS) bucket.

Step 2: Dive into the creation of a Cloud Fusion instance, setting up the groundwork for your data pipeline journey.

Step 3: Unveil the magic of Data Fusion as you craft a robust pipeline. Witness the transformation of data while ensuring sensitive information remains masked, ultimately loading it into BigQuery for further analysis.

Step 4: Elevate your data visualization game as you harness the power of Looker Studio, bringing your insights to life in a visually compelling manner.

Join me on this illuminating journey through the intricacies of ETL pipelines, empowering you to master data orchestration and visualization in the Google Cloud ecosystem.

Playlists
Google Agent Development Kit (ADK)
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