Companies have access to an increasing amount of customer data that can help them make business decisions, such as customer interests and buying habits. However, managing all of this data is often quite cumbersome, and manually reviewing it for accuracy is simply impossible due to the sheer size of the data.
Generating business intelligence reports based on incomplete data will result in reports that can't be relied on, so it's important for businesses to make sure that their customer records are as accurate as possible. Thankfully, data quality monitoring software provides an easy way to automate this process. To learn more about what data quality monitoring does and how it can help protect the integrity of your business's customer data, read on.
Initial Data Validation
The most important role that data quality monitoring software performs is checking the correctness of data when it's first added to your company's database server. For example, customer contact information such as phone numbers, email addresses, and addresses will be checked to ensure that the entered data appears valid. Any data that looks like it may not be valid will be flagged, alerting your employees that they need to manually review the data before it's added to the system.
Checking data for correctness as soon as it's entered prevents errors from propagating further. When bad data is used for analysis, the reports generated from analyzing the data will be incorrect — this makes the reports unreliable for use when making business decisions. Ensuring that data is manually reviewed and kept free of errors when introducing new records to your company's database will result in data analysis that's accurate and useful.
Periodic Checks for Stale Data
In addition to checking data when it's first added to the database, data quality monitoring software also prevents the records in your database from becoming incorrect due to age. Customers will periodically move or change their phone numbers, for example, so customer contact information tends to become less reliable over time.
When data is added to your database, the date that it was added will be recorded as well. Data quality monitoring software periodically checks for old data and flags it for manual review if it's more than a few years old. This prevents the data in your database from becoming stale, which helps keep the data relevant and useful for analysis.
Finally, data quality monitoring software also quarantines data that's potentially false. Manually reviewing data in order to correct records that are false can take some time, and your company's business intelligence department should be able to continue analyzing good data with minimal interruption while the incorrect data is being fixed.
The rest of your business shouldn't have to wait around while data is being corrected, so quarantining the data so that it's automatically excluded from analysis keeps your business intelligence unit operational while the slow task of correcting faulty data is being performed by other departments.
Overall, having access to data that's accurate means that the reports generated from that data will be more reliable and more useful for making business decisions. Data quality monitoring software automatically flags records that are incorrect or incomplete, allowing them to be corrected manually by your employees. If you're not keeping tabs on the integrity and accuracy of your data with data quality monitoring software, it's a good idea to start — investing in maintaining data accuracy means that your business intelligence department can easily generate reports that you can rely on.
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