Introduction to Data Analysis
Data analysis is the process of examining, cleaning, transforming, and modeling data to discover useful insights, inform conclusions, and support decision-making. It involves statistical techniques, data mining, and machine learning to extract meaningful patterns from raw data.
Key Steps in Data Analysis
- Data Collection: Gathering raw data from various sources such as databases, APIs, and IoT sensors.
- Data Cleaning: Removing duplicates, handling missing values, and correcting errors to ensure data quality.
- Exploratory Data Analysis (EDA): Using statistical summaries and visualizations to understand data distributions and relationships.
- Feature Engineering: Transforming raw data into meaningful features for machine learning models.
- Data Interpretation: Drawing conclusions based on statistical and analytical findings.