📊 Final Task: BI Analyst - Bank Muamalat

By Ahmad Raja Fadhil

📌 Project Overview

This project aims to analyze and enhance the sales performance of PT Sejahtera Bersama through a structured data-driven approach. By utilizing a dataset containing customer, product, order, and product category information, this project identifies patterns and trends that support strategic decision-making.

🛠 Tools & Technologies

• Python (Google Colab)
• Microsoft Excel
• Google Looker Studio
• SQL (for data analysis)

📂 Dataset

The dataset used in this project consists of several main tables:

1. Customer – Contains unique customer IDs and personal information.
2. Orders – Stores order details, including date and purchased products.
3. Product – Lists available products, including price and category.
4. ProductCategory – Contains product category names and abbreviations.

🔍 Data Processing Steps

1. Identify Primary Keys in each table to establish data relationships.
2. Create Relationships between tables using One-to-Many and Many-to-One concepts.
3. Build a Master Table by merging all datasets using Google Colab.
4. Data Cleaning to remove missing values and ensure data integrity.
5. Data Visualization using Google Looker Studio to extract sales insights.

📈 Key Insights

• Total Sales: Rp 1,754,750.57 with 11,654 orders.
• Top Category: "Robots" had the highest sales but a low number of orders.
• Sales Trend: The highest peak occurred in June 2021.
• Top City: Washington recorded sales of Rp 55.4K with 308 orders.

🎯 Strategic Recommendations

1. Enhance digital marketing efforts through email campaigns & social media ads.
2. Implement customer loyalty programs to increase repeat purchases.
3. Introduce product bundling to boost sales of high-value items.
4. Develop seasonal marketing strategies to capitalize on sales trends.
5. Expand into new markets to diversify revenue streams.

📜 How to Use

1. Clone this repository or download the .ipynb file to run in Google Colab.
2. Ensure the dataset is available and structured correctly.
3. Run the notebook to perform analysis and generate visual insights.

📬 Contact

For any questions or further discussions, feel free to reach out:
📧 Email: fadhilahmadraja@gmail.com
🔗 LinkedIn: linkedin.com/in/ahmadrajaf