Data Cleansing, Preparation and Enrichment
The key steps include understanding the data, assessing its quality, handling missing data, removing duplicates, standardizing and formatting, handling outliers, integrating data from multiple sources, validating the cleaned data, and maintaining documentation.
The goal of data enrichment is to enhance the depth and breadth of the dataset, enabling more comprehensive analysis and decision-making.