datemanipulation
Datamanipulation is the process of adjusting, transforming, or reorganizing data to make it suitable for analysis, storage, or presentation. It encompasses a range of operations that prepare raw data for downstream use, including cleaning, normalization, filtering, reshaping, and aggregation. Good datamanipulation enhances data quality, supports accurate reasoning, and preserves provenance.
Common techniques include data cleaning (removing duplicates, correcting errors, addressing missing values), normalization and standardization (scaling
Practically, datamanipulation is carried out with programming languages and tools such as SQL, Python libraries like
Challenges include handling missing or conflicting data, avoiding data leakage, ensuring privacy and security, and maintaining
See also: data cleaning, data wrangling, ETL, data governance, data quality.