Building an Automated Data Pipeline for Sales Data in Google Cloud | GCP Data Engineering Project
Welcome to our comprehensive tutorial on building an automated data pipeline for sales data using Google Cloud Platform (GCP). In this project, we'll guide you through the entire process of setting up a robust data pipeline that facilitates the seamless upload, storage, processing, and visualization of sales data.
🔹 Project Overview
This project demonstrates the integration of several GCP services to create an efficient and automated data pipeline for sales data. We'll show you how to:
Develop a web portal using Python Flask for uploading sales data files (CSV, Excel).
Store the uploaded files in a Google Cloud Storage (GCS) bucket.
Trigger a Google Cloud Function to process and load the data into BigQuery.
Use Looker Studio to create insightful dashboards and reports for data visualization.
Source Code - https://github.com/vishal-bulbule/sal...
Looking to get in touch?
Drop me a line at [email protected], or schedule a meeting using the provided link https://topmate.io/vishal_bulbule
Playlists
Associate Cloud Engineer -Complete Free Course
• Associate Cloud Engineer -Complete Fr...
Google Cloud Data Engineer Certification Course
• Google Cloud Data Engineer Certificat...
Google Cloud Platform(GCP) Tutorials
• Playlist
Generative AI
• Generative AI
Getting Started with Duet AI
• Getting started with Duet AI | Google...
Google Cloud Projects
• Google Cloud Projects
Python For GCP
• Python for GCP
Terraform Tutorials
• Terraform Associate Certification(00...
Linkedin
/ vishal-bulbule
Medium Blog
/ vishalbulbule
Github
Source Code
https://github.com/vishal-bulbule
#googlecloud #gcp
Watch video Building an Automated Data Pipeline for Sales Data in Google Cloud | GCP Data Engineering Project online without registration, duration hours minute second in high quality. This video was added by user TechTrapture 29 May 2024, don't forget to share it with your friends and acquaintances, it has been viewed on our site 12,590 once and liked it 266 people.