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 ...
You would be surprised to know that data enrichment solutions market is sizing up at a CAGR of 8.3 % by 2030, according to a report . The reason is the value of contextual data, which lead to success. If you want to create highly effective and personalized marketing campaigns, you need high-quality contact lists. Many-a-times, you have email IDs or contact lists, but a few may be incomplete. What if that contact list has more than half incomplete or wrong details? Certainly, this can weaken your marketing campaigns. And, you won’t be able to achieve what you think of. So, the main concern is data enrichment. This blog will help you understand how to enrich leads in your database for marketing campaigns. Let’s get started with defining what lead data enrichment is. Lead Data Enrichment Leads refer to the contact list of intended customers (who are interested in investing in the brand). And lead data enrichment is a defined strategy t...