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https://github.com/arnabsaha7/techretail-sales-analysis
https://github.com/arnabsaha7/techretail-sales-analysis
Last synced: about 1 month ago
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- Host: GitHub
- URL: https://github.com/arnabsaha7/techretail-sales-analysis
- Owner: arnabsaha7
- Created: 2024-11-11T04:40:43.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-11-11T05:30:47.000Z (3 months ago)
- Last Synced: 2024-11-11T05:31:08.678Z (3 months ago)
- Language: Jupyter Notebook
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# TechRetail Azure Data Pipeline Analysis



This project, **TechRetail Azure Data Pipeline Analysis**, provides a robust analysis of retail data via an Azure-based data pipeline. Leveraging Power BI and Databricks, it delivers interactive visualizations and insightful data workflows, covering key performance metrics and customer insights.
---
## 📂 Repository Structure
- **📊 PowerBI/**: Includes the Power BI report template (`.pbix`) with interactive dashboards and visualizations.
- **📑 PPT/**: Contains the main presentation file (`TechRetail_AzureDataPipeline.pptx`) and a PDF version summarizing the project findings.
- **📓 Notebook/**: A Databricks notebook that documents the data preprocessing, analysis, and insights generation process.---
## 📈 Dashboard Preview

---
## 🔍 Analysis Highlights
Below is a collection of key insights from the analysis:
| 
**Total Sales Per Quarter Per Year** | 
**Distribution of Transaction Amounts** | 
**Top Selling Products by Total Sales** |
|------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------|
| 
**Total Purchases vs Total Amount** | 
**Correlation Heatmap** | 
**Total Sales Growth Per Year** |---
## 📁 File Details
### 1. Power BI Template
The **PowerBI** folder includes a `.pbit` template for creating dynamic visualizations and insights. Key sections in the dashboard:
- **Sales Metrics**: KPIs on sales performance.
- **Regional Analysis**: Geographical insights to optimize strategy.
- **Customer Segmentation**: Visual breakdowns of customer demographics.### 2. Presentation
In the **PPT** folder:
- `TechRetail_AzureDataPipeline.pptx`: A structured presentation covering the project overview, methodology, insights, and conclusions.
- `TechRetail_AzureDataPipeline.pdf`: A PDF version for easy sharing.### 3. Databricks Notebook
The **notebook** file provides:
- Detailed data preprocessing and feature engineering steps.
- Exploratory Data Analysis (EDA) for uncovering trends and patterns.
- Code documentation for reproducibility.---
## 🚀 Getting Started
To view and explore the files:
1. **Power BI Report**: Open the `.pbit` file in Power BI Desktop.
2. **Presentation**: Access the PowerPoint or PDF for a concise overview.
3. **Databricks Notebook**: Open in Databricks to explore the analytical workflow.---
## ⚙️ Prerequisites
- **Power BI Desktop** for viewing the `.pbit` template.
- **Azure Subscription** for utilization of resources
- **Databricks Environment** with necessary libraries.---
## 📬 Contact
For questions or collaboration inquiries, reach out through my [GitHub profile](https://github.com/arnabsaha7) or via [Email](mailto:[email protected]).