ETL BigData

This repository contains a web application for performing ETL (Extract, Transform, Load) processes on data and saving it in a database. It utilizes Flask as a web framework and Elastic Search for logs.

ETL Process

The ETL (Extract, Transform, Load) process is a common data integration process used in data warehousing and analytics. Here’s a brief explanation of each step:

1. Extract:
   • The extract step involves retrieving data from various sources, such as databases, files, APIs, or web scraping.
   • In the context of this application, users can insert files in XLSX or CSV format to extract the data.
2. Transform:
   • The transform step involves cleaning, validating, and transforming the extracted data into a suitable format for analysis or storage.
   • This application provides functions for cleaning and managing the data, allowing users to apply transformations to the extracted data.
3. Load:
   • The load step involves storing the transformed data into a target database or data warehouse for further analysis and reporting.
   • The application saves the transformed data into a database for future retrieval and analysis.

Frameworks and Tools

The ETL_BigData application leverages the following frameworks and tools:

• Flask: Flask is a lightweight and extensible web framework used for developing web applications.
• Elastic Search: Elastic Search is a distributed, RESTful search and analytics engine capable of handling large amounts of data and providing powerful search capabilities.

Getting Started

To get started with the application, you need to install the required dependencies listed in requirements.txt. Run the following command to install them:

pip install -r requirements.txt

Running the ETL App

To run the ETL_App, execute the following command:

```python python app.py