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Bad Data: The Warning Signs

Data hygiene is an integral aspect of data management, and ensuring data quality is key to any successful data-driven business. A data set can be considered bad if it contains duplicate records, missing or incorrect data points or unstructured and inaccurate data. It takes almost no time for information to become outdated. For example, as soon as any member relocates, creates a new email address, or changes their phone number, your data instantly becomes outdated. 

The Benefits of High-Speed Connections

Identifying Bad Data To begin evaluating the status of your data, perform an audit or data analysis. Data auditing involves running validation tests to compare data against known values, in addition to looking for anomalies and inconsistencies in the data set. You can also check records for completeness, integrity, and accuracy by examining fields that should contain certain data types such as numbers or text strings. The first step in this process is to identify errors to resolve. Once you know what needs to be corrected, you can then take corrective action either manually or using automated tools.

Common Warning Signs of Bad Data

– Bounce back emails are an obvious sign that your data is inaccurate. If you’re conducting email outreach and a high number of emails are bouncing back, it’s probably time to take a closer look at your data.

– Review the quantity of return-to-sender mail your organization typically receives. Many organizations still utilize monthly mailer services, and any mail that is returned or undeliverable is a tell-tale sign of outdated contact information within your database.

– If it’s been more than a year since you last evaluated and cleaned your data, it’s probably time to revisit the process. Ideally, organizations should pursue data cleaning approximately twice a year.

Cleaning Your Data

Record and database size largely determines the most effective and realistic method for cleaning your data. Most of the time, a manual clean is not the ideal method for cleaning up your data. If your record size is less than 5,000 records, a manual clean may be attainable, though it will demand a significant investment of time and preserve the potential for human error. Automated hygiene tools are becoming the way of the future and the best approach to ensure your organization is operating in the most effective and efficient way. Data hygiene may seem like a tedious and painful process; however, dedicating resources towards data cleaning saves time and money in the long run by ensuring accuracy and organizational success. Maintaining accurate data records will help you make better decisions, improve customer relationships and increase overall business performance.

Maintaining Your Clean Data 

After your first cleaning, the data will only get easier to maintain. You should experience significantly fewer bounce backs and return-to-sender mailings allowing your focus to shift towards effectively reaching your organizational goals. It is still recommended your data undergo a thorough a clean once or twice a year, but it will get much easier to identify issues after you perform your first clean. 

Interested in automated data cleaning tools? Learn more about how Bumblebee Data can transform your data and help you achieve your goals in 2023.