Definition
Editing is the careful scrutiny of collected data to detect and correct errors, omissions, or inconsistencies before analysis. Coding is the process of assigning numerical or symbolic values to responses so that they can be grouped, compared, and statistically analyzed.

Introduction
Raw data are rarely ready for immediate analysis. They arrive scattered, incomplete, or inconsistent—like rough gemstones needing polishing before they reveal clarity. The editing and coding stages perform that refinement, transforming unstructured responses into an organized and analyzable dataset.

Explanation
After fieldwork, researchers examine questionnaires or transcripts for completeness and legibility. Editing corrects accidental omissions, illegible handwriting, or contradictory answers. It can be field editing—done daily by supervisors to catch early mistakes—or central editing, where specialists review forms in the office.

Once verified, data are coded. Each possible answer is given a numeric code (for example, “Gender: 1 = Male, 2 = Female”). For open-ended questions, responses are first categorized into thematic groups before assigning codes. Consistency in coding ensures comparability across cases. Modern software such as SPSS or R can generate automated codebooks, minimizing manual errors.

Editing and coding not only prepare data for computers but also enforce discipline—ensuring that what enters analysis truly reflects what was intended in the design.

Key Takeaways
Editing ensures accuracy; coding brings structure. Together they create the foundation for reliable statistical and qualitative interpretation.

Real-World Case
The Nielsen Company, before running television-viewership analytics, conducts multilayer editing of its household diaries and automatically codes thousands of program titles into standardized genre categories—guaranteeing uniform global reporting.
Reference: https://www.nielsen.com