Data preparation is the work of collecting, cleaning, joining, reshaping and validating data so it can be analysed or used by AI — typically most of the effort in any analytics project.
Also called: data wrangling, data manipulation, data cleaning
It covers connecting to sources, fixing types and formats, handling missing values, deduplicating, joining tables, deriving columns and checking quality rules.
Done by hand in spreadsheets it is slow and unrepeatable. Done as a versioned pipeline it can be scheduled, audited and reused — which is how ATX AnalyticsTable handles it.
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