Definition
ETL
Extract, Transform, Load (ETL) is a process used in data warehousing to collect data from different sources, transform it into a consistent format, and load it into a central repository for analysis and reporting.
Why ETL is Important
- Data Integration: ETL combines data from multiple sources into a single, unified view.
- Data Quality: It cleans and standardizes data, ensuring accuracy and consistency.
- Efficiency: Automates the process of moving and preparing data, saving time and reducing errors.
The ETL Process
1. Extract
- Definition: Extracting data means collecting it from various sources, such as databases, spreadsheets, or APIs.
- Challenges: Data may be in different formats or stored in incompatible systems.
- Extracting sales data from an SQL database, customer information from a CSV file, and product details from an XML file.
2. Transform
- Definition: Transforming data involves cleaning, standardizing, and converting it into a consistent format.
- Key Steps:
- Data Cleaning: Removing duplicates, correcting errors, and handling missing values.
- Data Standardization: Converting data into a common format (e.g., dates in YYYY-MM-DD).
