A professional specialized in identifying and correcting inaccuracies, inconsistencies, and errors in datasets to ensure the data is accurate, reliable, and ready for analysis. Role is crucial in ensuring data quality before it is used for reporting, business decision-making, or further analysis.

Data cleansing analysts use various techniques and tools to clean data, such as removing duplicate records, correcting formatting issues, handling missing or incomplete data, and standardizing data entries across different sources. Often work with data in different formats (e.g., spreadsheets, databases, APIs) and use tools like Excel, SQL, Python, or data cleansing software such as Trifacta or Talend.

Their task also include validating data against predefined rules, normalizing datasets, and ensuring that data complies with relevant standards or regulatory requirements. By ensuring that the data is accurate and consistent, data cleansing analysts play a key role in improving the overall integrity and usability of data for business intelligence, predictive analytics, and reporting.