Data Quality is one of the important modules in Data & AI, where this module ensures that the data used for decision making is in a clean and neat condition. Several internal processes include data standardization, master data mapping, ensuring there are no nulls or blanks, building golden master data records for analysis needs, and eliminating anomalies in data that cause bias in analysis.