Answer Posted / Ajay

1. Data Collection: Gathering data from various sources like databases, APIs, and files.n2. Data Cleaning: Removing missing values, duplicates, outliers, and formatting inconsistencies.n3. Data Transformation: Changing the structure of the data to make it more suitable for analysis.n4. Exploratory Data Analysis (EDA): Analyzing the data visually and statistically to understand patterns and relationships.n5. Model Building: Creating statistical or machine learning models to predict outcomes or uncover hidden patterns.n6. Model Evaluation: Assessing the performance of the model using appropriate metrics.n7. Model Deployment: Implementing the model in a real-world setting.

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