Skip to main content

Guide to data quality management

Jordyn Tetler

The more data, the better. Today’s organizations are collecting a vast amount of data from all areas of the business. Data is captured through transactions, website navigation, product development, and way more—and that’s just touching the surface. But, what value are all these insights providing your business if they are inaccurate?

Introducing: Data quality management. Your cornerstone to managing multiple streams of data, while ensuring high-quality insights are being leveraged for the most important business initiatives.

What is data management?

Data management is the process of acquiring, validating, storing, protecting, and processing data.

While a data management program is crucial to streamlining business insights, data quality becomes its right-hand. Enter: Data quality management.

As you start thinking about data quality management, it’s important to review how accurate your information is in each stage of the data management process. Is your data accurate at the point of collection? Are you confident in leveraging the insights found in your current database?

An effective data management strategy is crucial for today’s organizations who are looking to stay one step ahead of their competition. When you lay a foundation of data quality, you can empower your business to make better and faster decisions. More importantly, you can leverage that competitive edge as you shift with the everchanging market.

Why data quality is so important to data management

Data quality is a fundamental component to the success of a data management program. Think about it: How can you or your team effectively manage data that could be inaccurate and untrustworthy? Our research has found that 50 percent of organizations say their data is inaccurate due to human error.

What’s more, a complete and trustworthy database gives you confidence that you are leveraging accurate customer insights to drive business opportunity. You can do this through data validation and data enrichment capabilities.

Top benefits of data quality management

It’s no secret data quality management is a key driver when it comes to successful business outcomes. Organizations across all industries are seeing the benefits of data management, including:

• Improved customer experience.
• Better insight for decision-making.
• Allow for more innovation.
• And, way more!

Data quality management solutions

As you look for the best data quality management solution for your business, it’s important to first consider what tools will be easily adopted by your team, what your business and data goals are, and most importantly, what your budget is like.

A well-suited data quality management solution enables you to monitor data in real time, automating your data management practices and ensuring each and every record is reliable. Here are some key functions of a data management software:

• Data profiling and discovery
• Data enrichment
• Data standardization
• Data monitoring

Best practices for data management

As your organization begins to adopt data management practices, it’s important to remember that managing data should be an ongoing discipline. Let’s dive into the best practices:

1. Start with data quality.
2. Build in data governance.
3. Hire a CDO.
4. Democratize data.
5. Teach data skills.

Empower your business to adopt data management through these best practices. Before you know it, your data will be used across the entire enterprise to make better decisions, streamline operations, and improve customer experience, all while watching your bottom-line growth take off.

Experian can help you take your data to the next level with our best-in-class data quality management solution.

Talk with an expert today