ETL (Extract, Transform, Load) is a data integration process that enables businesses to collect data from multiple sources, convert it into a structured format, and load it into a centralized database or data warehouse for analysis. ETL is a key component of big data analytics, business intelligence (BI), and cloud-based data processing.

The ETL process consists of three main stages:

• Extract: Data is retrieved from various sources such as databases, APIs, cloud storage, or flat files.
• Transform: The raw data is cleaned, standardized, and formatted to match the target system’s structure.
• Load: The processed data is stored in a data warehouse or cloud-based analytics platform for reporting and insights.

Modern cloud-based ETL solutions allow organizations to automate data workflows, scale processing power dynamically, and improve data accuracy, making it easier to analyze vast amounts of information for AI-driven decision-making, fraud detection, and predictive analytics.