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https://github.com/thunchanokbow/inventory-amazon
Inventory value is also important for determining a company's liquidity, or its ability to meet its short-term financial obligations. A high inventory value can indicate that a company has too much money tied up in inventory, which could make it difficult for the company to pay its bills.
https://github.com/thunchanokbow/inventory-amazon
azure bigquery cloudcomposer clouddatabase cloudstorage compute-engine dataproc postgresql powerbi pyspark-sql python3
Last synced: 3 days ago
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Inventory value is also important for determining a company's liquidity, or its ability to meet its short-term financial obligations. A high inventory value can indicate that a company has too much money tied up in inventory, which could make it difficult for the company to pay its bills.
- Host: GitHub
- URL: https://github.com/thunchanokbow/inventory-amazon
- Owner: thunchanokbow
- Created: 2023-09-14T05:21:08.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2023-10-15T16:26:31.000Z (about 1 year ago)
- Last Synced: 2023-10-16T16:12:03.568Z (about 1 year ago)
- Topics: azure, bigquery, cloudcomposer, clouddatabase, cloudstorage, compute-engine, dataproc, postgresql, powerbi, pyspark-sql, python3
- Language: Jupyter Notebook
- Homepage:
- Size: 21.3 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
Amazon's Inventory of Clothes
============
Let's find out from the dataset of Amazon's e-commerce company whether there are enough products to meet demand or excessive inventory that leads to loss of sales opportunities and revenue.## Contents
[PostgreSQL Database](sections/01-postgres.md) managed database on Azure
- [Azure Database for PostgreSQL flexible server](sections/01-postgres.md)
[Data Collection](Inventory2Q2022.ipynb) with PySpark
[Data Pipeline](sections/02-data-pipeline.md) extract transform load
- [Google Cloud Composer](sections/02-data-pipeline.md#Create-Cloud-Composer) provides running Apache Airflow to automate tasks
- [Google Cloud Storage](sections/02-data-pipeline.md#Create-Bucket) (Data Lake)
- [Google Cloud Dataproc](sections/02-data-pipeline.md#Create-Cloud-Dataproc) managed Hadoop and Spark cluster
- [Google BigQuery](sections/02-data-pipeline.md#Create-Dataset) (Data Warehouse)
[Data Visualization](sections/03-data-visualization.md) building dashboard with Power BI Desktop
![11](/images/dashboard.jpeg)![13](/images/0-Data-architecture.png)
![12](/images/cover-0.PNG)
Get more dataset information:
https://www.kaggle.com/thedevastator/datasets