# sriram-118/retail-sales-data-pipeline-business-analytics-dashboard architecture

> Architecture diagram of the GitHub repository sriram-118/retail-sales-data-pipeline-business-analytics-dashboard, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-25). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard
- Repository: https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard

## Overview

This repository presents a retail-sales analytics workflow: CSV sales and dimension data are ingested, cleaned, transformed into a relational star schema, and used for an interactive Power BI dashboard. The tree contains the four CSVs and the PBIX, but no Python or database source, so those documented runtime stages have no supported source paths; their internal wiring is represented only at the documented workflow level.

Main entry points: [`Final Output.pbix`](https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard/blob/main/Final%20Output.pbix) (Power BI Dashboard), [`fact_sales.csv`](https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard/blob/main/fact_sales.csv) (Sales Facts), [`dim_customer.csv`](https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard/blob/main/dim_customer.csv) (Customer Dimension), [`dim_date.csv`](https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard/blob/main/dim_date.csv) (Date Dimension)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_inputs["Data Inputs"]
  node_sales["Sales Facts<br/>[fact_sales.csv]"]
  node_customers["Customer Dimension<br/>[dim_customer.csv]"]
  node_dates["Date Dimension<br/>[dim_date.csv]"]
  node_products["Product Dimension<br/>[dim_product.csv]"]
end

subgraph group_pipeline["Data Pipeline"]
  node_ingest["Python Ingestion"]
  node_clean["Data Cleaning"]
  node_transform["Data Transformation"]
  node_warehouse[("Star-Schema Database")]
end

subgraph group_analytics["Analytics"]
  node_dashboard["Power BI Dashboard<br/>[Final Output.pbix]"]
end

node_user(("Analyst"))

node_sales -->|"ingested by"| node_ingest
node_customers -->|"ingested by"| node_ingest
node_dates -->|"ingested by"| node_ingest
node_products -->|"ingested by"| node_ingest
node_ingest -->|"passes data"| node_clean
node_clean -->|"passes data"| node_transform
node_transform -->|"loads data"| node_warehouse
node_warehouse -->|"provides analytics data"| node_dashboard
node_user -->|"analyzes results"| node_dashboard

click node_sales "https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard/blob/main/fact_sales.csv"
click node_customers "https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard/blob/main/dim_customer.csv"
click node_dates "https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard/blob/main/dim_date.csv"
click node_products "https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard/blob/main/dim_product.csv"
click node_dashboard "https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard/blob/main/Final%20Output.pbix"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_sales,node_customers,node_dates,node_products toneBlue
class node_ingest,node_clean,node_transform,node_warehouse toneAmber
class node_dashboard toneMint
class node_user toneIndigo
```

## Components

### Data Inputs

- [Sales Facts](https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard/blob/main/fact_sales.csv): `fact_sales.csv`
- [Customer Dimension](https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard/blob/main/dim_customer.csv): `dim_customer.csv`
- [Date Dimension](https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard/blob/main/dim_date.csv): `dim_date.csv`
- [Product Dimension](https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard/blob/main/dim_product.csv): `dim_product.csv`

### Data Pipeline

- **Python Ingestion**
- **Data Cleaning**
- **Data Transformation**
- **Star-Schema Database**

### Analytics

- [Power BI Dashboard](https://github.com/sriram-118/retail-sales-data-pipeline-business-analytics-dashboard/blob/main/Final%20Output.pbix): `Final Output.pbix`

### Other components

- **Analyst**

## Connections

- Sales Facts → Python Ingestion: ingested by
- Customer Dimension → Python Ingestion: ingested by
- Date Dimension → Python Ingestion: ingested by
- Product Dimension → Python Ingestion: ingested by
- Python Ingestion → Data Cleaning: passes data
- Data Cleaning → Data Transformation: passes data
- Data Transformation → Star-Schema Database: loads data
- Star-Schema Database → Power BI Dashboard: provides analytics data
- Analyst → Power BI Dashboard: analyzes results