Datavask refers to the process by which a company reviews, corrects, and updates its data to ensure that it is accurate, consistent, and usable. Often it is about removing duplicates, correcting errors, standardizing formats and enriching data with missing information.
Purpose
The goal of data washing is to increase data quality so that the company can make better decisions, improve customer contact and reduce costs associated with incorrect information. Bad data can, for example, lead to wasted marketing, errors in reporting or loss of potential customers.
Examples of data laundering
- Fjernelse af dubletter i en kundedatabase
- Standardization of addresses, telephone numbers and e-mails
- Correcting spelling errors in names or cities
- Updating outdated information, e.g. contact persons or CVR numbers
- Adding missing data from external sources
Anvendelse
Data washing is used in many contexts, especially within CRM-systemer, marketing, financial management and reporting. For companies with large amounts of customer data, it's an important discipline to ensure that campaigns reach the right people and that sales teams work from valid information.
Metoder
There are both manual and automated methods for data laundering. Smaller companies can often handle the process in spreadsheets or via simple scripts, while larger companies use dedicated tools and integrations that can validate data against public registers (e.g. CVR in Denmark).