Data Inspection: Checking data types, missing values, duplicates, summary statistics
Univariate Analysis: Distributions, outliers, central tendency (mean, median, mode)
Bivariate/Multivariate Analysis: Correlations, relationships between variables
Data Profiling: Understanding data structure and quality
Numerical Data: Continuous vs discrete, scaling, normalization
Categorical Data: Nominal vs ordinal, encoding techniques (label, one-hot)
Datetime Data: Parsing, extracting features (year, month, day), handling time zones
