Data Quality Management: Definitions & Professional Tips

There are thousands of companies across the United States that are just now digitizing their data systems. They are going paperless and starting to apply rudimentary analytics to streamline their business models. In addition to prioritizing storage and security, these companies need to focus more on the quality of the data they are now using and accessing. Quality is an aspect of data that is frequently ignored but can end up making or costing a company thousands of dollars over a short period of time.

What is data quality?

Data quality is the ability of data to meet a number of thresholds that make that data useful for a company. Quality of data involves accuracy, relevance, and the frequency of updating data. Companies cannot use data that is inaccurate or has not been updated in years. They need relevant data that will help them make decisions and choose the best marketing, expansion, and production strategies. Data quality management is the process by which companies use labor and technology to review data and keep its quality as high as possible for as long as possible. Effective data management can result in companies saving money and charging less for their services over time.

Use the latest technology
One helpful tip for better quality of data is to always use and invest in the latest technology. Individuals should scour the internet and trade publications for the most advanced data technology available. This technology often has systems that help individuals review their data to spot any errors or problematic trends. These issues can quickly be corrected if they are pointed out in an adequate amount of time. However, technology can be expensive and foreign to many individuals who have not been utilizing data for years. As a result, companies need to have regular meetings where individuals pitch their plans for using money on quality management technology as carefully and intelligently as possible.

Set a governance structure
A governance structure is essential for any developments to occur in data management. This structure should have either one or more individuals be held responsible for all aspects of data. The hierarchy should be widely available and should include contact information so that employees at the company know where to go if there is any sort of problem with quality. Holding an individual or group of individuals responsible can help ensure that changes occur in a timely manner. If there are any significant quality problems, upper management will know exactly who they should talk to in order to remedy the problem.

Companies must start their quest for better quality with an assessment of their assets and employees. They need to know who should be in charge and what everyone’s roles should be. Companies also need to decide how much money they can spend for technology and ensure that their numbers go up on a regular basis. Keeping technology spending high can ensure that a company will be able to keep their quality standards high and increase the chances for success int heir particular field.