🏥 Databricks Optical Campaign for Hoya Products

📄 Project Overview

This project focuses on leveraging Databricks to identify and engage customers who purchased Hoya products from Ótica Holy Glasses before 2024. The goal is to re-establish contact with these customers for potential new purchases or product upgrades.

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🎯 Objectives

• Customer Identification: Extract a list of customers who have previously purchased Hoya products.
• Data Transformation: Process and transform the data to prepare for targeted marketing campaigns.
• Campaign Execution: Utilize the transformed data to reach out to customers for potential re-engagement.

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🛠 Technologies Utilized

• Databricks: Unified analytics platform for data engineering and machine learning.
• PySpark: Python API for Apache Spark, used for large-scale data processing.
• SQL: Structured Query Language for querying and managing relational databases.
• Pandas: Python library for data manipulation and analysis.

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📈 Workflow Diagram

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📂 Repository Structure

📦 Databricks-SQL-Optical-Campaign
 ┣ 📜 Hoya_Campaign_SBC.ipynb   # Jupyter Notebook with analysis and code
 ┣ 📜 Hoya_Campaign_SBC.sql     # SQL script for data analisys and transformation
 ┣ 📜 workflow.png              # Visual representation of the data workflow
 ┗ 📜 README.md                 # Project documentation

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🚀 Getting Started

1. Clone the Repository:

   git clone https://github.com/RenanBjj/Databricks-SQL-Optical-Campaign.git
   cd Databricks-SQL-Optical-Campaign

2. Set Up Your Environment:

   • Ensure you have access to Databricks and an appropriate workspace.
   • Install the necessary dependencies:

     pip install pyspark pandas

3. Run the SQL Script:

   • Open the Hoya_Campaign_SBC.sql file and execute it within your SQL environment or Databricks.

4. Analyze the Data:

   • Open Hoya_Campaign_SBC.ipynb in Jupyter Notebook or Databricks and follow the analysis process.

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📬 Contact

For questions or collaborations:

• GitHub: RenanBjj
• LinkedIn: Renan Marques Rodrigues
• Email: renan.marques@example.com

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🚀 Developed with passion for data engineering and analytics!