Bad Data: The Warning Signs

Data hygiene is integral to 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. Even more challenging, it takes almost no time for information to become outdated. For example, when a member relocates, creates a new email address, or changes their phone number, your data instantly becomes outdated.

The Benefits of High-Speed Connections

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 take corrective action manually or using automated tools. Learn more about tackling common data hygiene challenges.

Common Warning Signs of Bad Data

• Bounce back emails: 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.
• Return-to-sender mail: Review the quantity of return-to-sender mail your organization typically receives. Many organizations still utilize monthly mailer services, and any returned or undeliverable mail is a tell-tale sign of outdated contact information within your database.
• Yearly Data Cleaning: 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.