Why is Data Cleansing so important?
Incorrect or inconsistent data can be costly as it results in false conclusions and misdirected investments. It is therefore in your best interest to ensure that the data you hold is free from any potential errors, dupes and format inconsistencies. Data Cleansing seeks to ensure this.
At Dataconversion we systematically examine data for flaws by using rules, algorithms, and look-up tables. High-quality data that has undergone rigorous cleansing and testing adds value throughout the organisation and enables accurate management information reporting with a single version of the truth when it comes to the data.
What is Data Cleansing?
Data Cleansing refers to the process of detecting, correcting or removing incomplete, inaccurate or duplicated records from a dataset. The aim of cleansing a dataset is to achieve consistency with similar datasets.
Inconsistencies detected are often the result of human error or corruption caused either during initial capture, migration between systems or inconsistent data processing. The goal of data cleansing is to achieve consistent, complete, accurate and uniform data. Data cleansing is often considered to be the most important aspect of data quality management.