There are a number of tools like OpenRefine, Drake, TIBCO Clarity, Winpure, Cloudingo and Data Cleaner etc. used for removing errors or corruptions from data automatically. Companies come with unique data cleansing solutions for your business. Certainly, it is analysed by assessing your requirements. Once cleared, the cleaning company tailors solutions. It may require customising tool for filtering, capturing and removing inconsistencies from a bulk of datasets. This doing requires you to have a stronghold on any programming language, MIS and data science experience. The perfect combination of these all helps you to have a customised tool for data cleansing.
Data Migration, which requires data upload, capture, import, & export, can be done through Hevo Data, SAP, Fivetran, Matillion, Stitch Data, AWS Data Pipeline, Xplenty, IBM Informix, & Azure Document DB
Data Collection, which is all about pooling datasets in a virtual space or storage, can be done with interview, survey, target group, case studies, observations, online polling, checklists, usage data etc.
Data De-duplication, which refers to removing dupes or similar entries with TrustMaps, Druva Data Resiliency Cloud, etc.
Data Verification, which requires validating datasets to use further, which can be done through Datameer, Talend, Informatica, ICEDQ, Datagaps ETL Validator, DbFit, Data-Centric Testing, etc.
Data Normalisation, which is to complete abbreviations using Table Analyzer, Normalizer or manually
Data Appending, which lets you complete any contact detail by integrating contextual details like Name, Last Name, Email IDs, Zip Code, etc., can be done with data finder or outsourcing companies’ customized tools.
Some useful links
Data Cleaning Steps and Techniques.