Data analysis is a systematic process that involves cleaning, processing, transforming, and understanding data to extract meaningful insights. It is a crucial aspect of various fields, including data science, business intelligence, and scientific research. The primary goals of data analysis are to summarize data, identify patterns, and uncover hidden relationships within the data set.

There are several types of data analysis, including descriptive, diagnostic, predictive, and prescriptive analytics. Descriptive analytics answers questions about what has happened in the past, while diagnostic analytics seeks to understand why certain events occurred. Predictive analytics forecasts future outcomes based on historical data, and prescriptive analytics provides recommendations for decision-making based on the analysis ³⁵.

Tools like Python, along with libraries such as pandas and Jupyter Notebook, are commonly used for data analysis due to their efficiency and ease of use ². Data cleaning is also a vital step, as real-world data is often messy and requires thorough preparation before analysis can take place ¹.