Hugging Face's logo

Spaces:
PranavSharma
/
TurnoverForecasting
Sleeping

App Files Community
TurnoverForecasting
File size: 3,519 Bytes 
e4f4b02
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
 
---

title: TurnoverForecasting
emoji: 📊
colorFrom: blue
colorTo: red
sdk: gradio
sdk_version: 5.22.0
app_file: app.py
pinned: false
license: mit
short_description: Forecasting SAP SE Revenue with AI
---


# 📊 AI-Powered Turnover Forecasting for SAP SE

## 🚀 Project Overview

This project delivers **AI-driven revenue forecasting** for **SAP SE** using a **univariate SARIMA model**. The focus is to demonstrate how reliable forecasts can be achieved with **minimal data** — only historical turnover — making this approach powerful for both large enterprises and **resource-constrained settings**.

---

## 📌 Why Univariate Forecasting?

- 🔎 **Focus on one key variable — Revenue**
- ✅ Ideal when limited data is available  
- 🧠 Easier to interpret and communicate results  
- 🚀 Fast to train, test, and deploy  
- 💡 Great for early-stage AI adoption and small business analytics  

---

## 🏢 Why SAP SE?

- SAP SE is a **global leader in enterprise software**  
- Accurate revenue forecasts support **strategic planning, risk management, and growth**  
- As a digital-first company, SAP is ideal for showcasing **AI integration in financial operations**

---

## 🛠️ Technical Approach

- **SARIMA** model (Seasonal ARIMA) for time-series forecasting  
- Forecast horizon: **1 to 6 quarters**  
- Built-in **walk-forward validation**  
- **Gradio UI** for interactive forecasting  
- Visuals powered by **Plotly**

---

## 📊 Dataset

- Source: [Top 12 German Companies Financial Data (Kaggle)](https://www.kaggle.com/datasets/heidarmirhajisadati/top-12-german-companies-financial-data)  
- Focused subset: **SAP SE revenue over time**  
- Realistic industry dataset for enterprise-level modeling

---

## 🎯 Features

- Predict revenue trends with confidence intervals  
- Dynamic forecasting by adjusting horizon and confidence level  
- Interactive and mobile-friendly layout (single-column Gradio)  
- Insightful visual comparisons: Training, Validation, Test & Future Forecasts

---

## ⚙️ How to Run

```bash

git clone https://github.com/Sharma-Pranav/Portfolio.git

cd projects/TurnoverForecasting

pip install -r requirements.txt

python app.py



---



## **📌 Results**  

- **Accurate Accurate revenue forecasting for SAP SE for better financial planning. **  

- **Optimized financial planning & business strategy insights.**  

- **Walk-Forward Validation ensures model reliability over time.**.  

```

---

## 🌐 Try It Live on Hugging Face

Experience the project **without installing anything**!

🚀 Just head to the hosted interactive demo:

👉 **[Launch the Forecasting App](https://huggingface.co/spaces/PranavSharma/TurnoverForecasting)**

[![Hugging Face Space](https://img.shields.io/badge/🤗%20View%20on%20Hugging%20Face-blue?logo=huggingface)](https://huggingface.co/spaces/PranavSharma/TurnoverForecasting)

---

### 🔍 What You Can Do:

- 📅 **Select Forecast Horizon** – Choose how many future quarters (1–6) to predict  
- 🎯 **Adjust Confidence Level** – See uncertainty intervals dynamically  
- 📈 **Visualize Forecasts** – Instantly view training vs. validation vs. future forecasts  
- 📲 **Use on Any Device** – Mobile-optimized for fast access anywhere  

---

📌 **Developed by:** Pranav Sharma
📆 **Project Start Date:** February 2025  
📁 **Repository:** https://github.com/Sharma-Pranav/Portfolio/