1. Data Cleaning: Removing noise and correcting errors to improve data quality. 2. Data Transformation: Converting raw data into a format suitable for analysis. 3. Data Analysis: Using statistical methods and machine learning algorithms to extract meaningful insights. 4. Visualization: Creating visual representations such as graphs and charts to make the data more understandable.
