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Data hygiene is the process of achieving "clean" data—information that is error-free, updated, consistent and factual. It is important to maintain clean data for many reasons. Dirty data can steer sales and marketing efforts in the wrong direction and can hurt an organization’s revenue and productivity. On the other hand, clean data can be analyzed and processed in order to find relevant conclusions for the company. For example, as part of a business interaction, business data, or b2b data, can be collected and analyzed in order to figure out how to best optimize the business relationship between the two companies. By following data hygiene best practices, organizations can ensure their data sources produce relevant and clean data at the point of entry, and that clean data is maintained and stored throughout all processes.
As companies collect and process larger amounts of big data, the importance of data management and hygiene will only continue to grow. Ongoing data collection creates larger pools of data, and also creates larger opportunities for bad data to be collected or stored. A data auditing or data cleansing system is the usually first step to ensuring proper data hygiene. These systems can automatically analyze data entries and delete any duplicate records they find. Such systems can also identify missing customer data that changes often, such as contact information like email addresses and phone numbers. After the system flags for missing data, organizations can reach out to these customers, thereby giving them knew opportunities to engage and support them.
Maintaining high quality data is critical to business success as it saves both time and money by keeping updated records. Organizations should continually review their databases in order to ensure data hygiene. This is an arduous task that requires a lot of man hours to complete, or a company could instead set up automated maintenance systems, such as those that use machine learning. These systems can perform data cleanses in real time as the data is ingested and transported to new locations. Maintaining data throughout its lifecycle is also imperative to ensuring proper data hygiene.
Maintaining data hygiene practices is important because: