The database management is uniformly significant in all organisations, whether profit or non-profit. Essentially most of the organisations develop their own database management system for hiring the candidates, but managing such a massive database is time and money consuming process. Therefore, now a day considerable number of organisations outsource database management to the recruitment process outsourcing companies.
Recruitment Process Outsourcing (RPO) companies procure the team of professionals to perform the task of database management. According to the client's business sector the job of database management is assigned to a team member, who holds expertise in the industry. That expert either individually or with a team handles the client organisation's requirement of database. The database consists of candidate's CVs, and contact details therefore, accuracy is very crucial factor from the aspect of recruitment.
The whole set of data is valuable for the organisation, but it does not ensure the smoothness of its usage. For utilisation of the data, by management it needs to be accurate, and meaningful. Database cleansing or cleaning or scrubbing is the procedure of analysing, auditing and removing inaccurate data and make it ready for managerial usage. This technique helps the company to maintain accuracy, integrity, validity, consistency, uniformity, completeness and density of the information. It is very important to clean the database occasionally to maintain its integrity. As the incorrect, invalid and inconsistent data leads to false or out dated information.
Database cleansing can be very elaborate process depending on the method chosen by the RPO Company. They should plan carefully to pick the method of data cleansing to achieve the elimination of unwanted and invalid data. Primarily, the process of database cleansing can be classified in three methods, which are as follows:
- Automated Data Cleansing Method
- Manual Data Cleansing Method
- The Combined Data Cleansing Method
The selection of data cleansing method is truly based on the amount of data, cost involved in data cleansing, and fixing of errors in data. Data cleansing is a monotonous and time taking exercise which requires a methodical strategy, selection of the best method, and basic understanding of the client's requirement.