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Data is only as good as the quality behind it. The saying ‘garbage in, garbage out’ holds true. If you use inaccurate data for analytics, customer insight, or reporting, your institution is open to poor customer experience, inefficiency, or even non-compliance. While many agree that trusted data is a must, not everyone is making the investments needed to make that a reality. Here are three ways to justify a data management initiative within your institution.

Focused on the needs of government agencies, the DGVision conference empowered federal employees with new insights, best practices, and education around starting and optimizing data governance initiatives. Experian joined business leaders in both private and public sector companies for meaningful conversations about all things data governance.

In our new video series “What’s up Wednesday,” we’ll give you a quick video overview of a concept that we often get questions about at Experian Data Quality.

What’s up with… phone validation? Verifying phone numbers is a critical aspect of your overall data quality strategy. The phone can be an excellent way to reach out to your customers, but if your organization isn’t handling them properly you could be putting yourselves at risk.

When it comes to consumer privacy and phone numbers, the Federal Communications Commission (FCC) has put a number of regulations in place to protect consumers. Anyone collecting this sensitive information must be aware of the Telephone Consumer Protection Act (TCPA) – otherwise your organization could face poor customer satisfaction, fines or lawsuits.

To ensure successful email delivery, reduce the chances of being filtered out by an email service provider (ESP), and avoid becoming blacklisted as a spammer, organizations need to ensure the accuracy of the email data held in their mailing lists. Learn more about Experian’s industry-leading technology which verifies business domains, international domains, and consumer domains like Yahoo!, Gmail, Hotmail, and more.

We find a growing number of businesses are either looking to start or optimize data governance programs to better control data, but at Data Governance Winter Conference, we learned that there are often two major roadblocks to implementing or optimizing your data governance program.  Explore how you can navigate these challenges. 

Determining what type of data quality tools your organization needs depends upon how sophisticated your data quality strategy is. For some companies, a simple data quality approach may be fine, but other organizations may need a very advanced level of data accuracy and data management.

Regardless of your organization’s specific needs, there are a few key universal data quality considerations that are important for any effective approach. Here are six tools that can help with your data quality strategy.

1. Data cleansing: Data cleansing tools are needed when an organization’s data must meet specific domain restrictions, integrity constraints or other business rules. These types of tools provide accurate information for business use. Examples include address verification, email verification, phone validation, etc.