Data manipulation refers to the process of changing, organizing, or converting raw data into a structured or usable format for analysis or other purposes. This can include tasks like sorting, filtering, aggregating, merging, or transforming data sets to suit specific needs or to prepare the data for further analysis. Data manipulation is often one of the first steps in the data analysis workflow and is essential for cleaning and pre-processing data to ensure its quality and reliability. While the term generally carries a neutral or positive connotation in contexts like data analysis, it can also refer to the unethical or deceptive practice of altering data to mislead or produce false results. Therefore, data manipulation can be a double-edged sword: on one hand, it's a necessary process for turning raw data into actionable insights; on the other hand, when done irresponsibly, it can distort facts and compromise the integrity of conclusions drawn from the data.