What is the data science lifecycle?

The data science lifecycle has 6 stages:

1. **Business Understanding** — define the problem
2. **Data Collection** — gather relevant data
3. **Data Cleaning** — handle missing values, outliers, duplicates
4. **EDA (Exploratory Data Analysis)** — visualise and understand patterns
5. **Modelling** — train and evaluate ML models
6. **Deployment** — put model into production

Each stage is iterative — you often go back to previous steps.