A Business Owner’s Guide To Monitoring Data Quality

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By Jacob Maslow

If your enterprise has high-quality data from which to make timely business decisions, you have the opportunity for greater profits, better worker productivity and workflow, and customer engagement and loyalty.

What is Quality Data?

Quality data is correct, thorough, in a format that can be used for analysis, kept current, uniform between your enterprise’s departments, and useful for all employees.

Also, quality data does not have duplications, such as one customer with two different accounts. Quality data also gleans information from unique and powerful sources to get an accurate picture of all aspects of your enterprise, including sales, production, shipping and/or transport, and customer demographics. Quality data can save your enterprise money and help you nimbly seek the best profit centers.

Data Governance

Since data quality is key to navigating a successful enterprise, one large task is to monitor and manage your data to keep it accurate and reliable. Managing and monitoring data is called “data governance.” Data has a lifespan. You collect, store, utilize, and change data as needed. You even need to decide when specific data is no longer needed. Every employee in your enterprise must be responsible for quality data.

Specific Data Quality Monitoring Tasks

One of the first tasks to get on board with monitoring data is to have a team responsible for data governance and to have that team train the rest of your staff. Everyone needs to understand their part in maintaining and creating high-quality data. Your data governance team needs to define what high-quality data that can drive business decisions looks like at your firm. The data governance team will create a system to explain the rules for high-quality data. They also need to have a system to audit data regularly. A system needs to be put in place to report data as well. Erroneous data needs to be fixed and/or cleansed. Firewalls need to be installed where possible to keep inaccurate data out from the start. An example of the latter is software-driven format guides.

Monitoring Data Quality Through Automation

As you can see, the tasks of a data governance team can swallow up the precious time of the employees chosen for the data governance team, leaving them little time for their other enterprise tasks. Working with a data quality software provider to automate data quality tasks helps keep your DG team more productive. Sophisticated software can be developed and employed to monitor data for anomalies and errors by utilizing your data governance team’s data rules. Data can be monitored as input into the system in real-time, flagging and correcting mistakes. The data can be profiled automatically automatically to identify potential mistakes and view changes over time. Also, data management software can generate alerts if significant anomalies occur. Regular data quality audits can inform your data governance team of the need for intervention and improvement.

Maintaining a quality data stream to make business decisions, maintain productivity, and aid customer loyalty requires a data governance team. Automated software that assists the data governance team in monitoring, auditing, and profiling your data regularly will save money and enhance their productivity. Automated data quality software systems also provide yet another assurance of the quality data that helps your enterprise enhance profits, find new profit centers, improve market positioning, maintain the productivity of your entire team, and improve customer engagement.

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