Data cleansing or scrubbing is an integral part of data management. Typically, it requires focus on maintaining 99.99% accuracy, consistency, and authenticity of data sources. Businesses, these days, are more inclined to maintain data hygiene because they cannot afford the catastrophic effects of bad decisions. It’s obvious that bad or noisy data leads to bad decisions. So, this data cleanup process is emerging as the backbone of businesses’ forecasting and strategy-making teams. Here, some of the most common data cleansing techniques are shared. Let’s start introducing them. Proven Data Cleansing Techniques for Accurate Data Let’s catch up with some of the proven techniques to maintain hygienic data. 1. Data Validation A study by Experian proves that 83% of organizations trust data quality to be critical for their success. This goal cannot be achieved unless you know how to validate data. It is a significant factor in cleansing data. When the data is stored, certain criteria are made ...