What does "data analysis" primarily involve?

Data analysis primarily involves inspecting and modeling data to support decision-making because it encompasses a range of activities aimed at understanding and interpreting data in order to draw conclusions and inform decisions. This process often includes data manipulation, statistical analysis, and interpretation of results, all of which are crucial for making informed choices based on data insights.

The core of data analysis is to transform raw data into meaningful information that can help identify trends, patterns, and insights. This is essential in various fields, such as business, healthcare, and science, where data-driven decisions significantly impact outcomes. Analyzing data allows organizations and individuals to assess situations, predict future trends, and make strategic choices that are backed by evidence.

In contrast, cleaning and formatting data for storage focuses more on preparing data for analysis rather than the analysis itself. Modeling data to generate visualizations is a specific technique that can be part of the analysis process but doesn't encompass the full scope of what data analysis is intended to achieve. Collecting data from multiple sources is a preliminary step that precedes analysis and is focused on gathering rather than interpreting data.