Data Visualization Explained: What It Is and Why It Matters

Data visualization is a crucial step in data science for conveying insights, which is often more important than the analysis itself. The practice involves transforming any type of data into a visual representation, with historical examples including ancient Babylonian maps and John Snow's 1854 cholera map. Two core principles for creating effective visualizations are precision and flexibility; a visualization should have a specific, well-defined purpose and not try to show too much at once. The creation process is iterative and benefits from targeted feedback from a small, diverse group of reviewers to ensure the final product is clear and useful for its intended audience.