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Agentic AI increases autonomy—and risk—making data quality a strategic foundation. Learn three principles for building trusted, scalable data quality in an agentic AI future.

In today's data-driven world, companies across industries recognize data as a powerful asset for decision-making. But what constitutes reliable data? How can you assess whether the data your business relies on is mature and dependable enough to instill confidence in your team and drive strategic decisions? Understanding the 10 characteristics of data quality makes it easier to evaluate and enhance the quality of your data, which will serve as a solid foundation for your organization's growth and success. What are the 10 characteristics of data quality? The criteria for good data quality comes down to 10 data characteristics, which are: Accuracy Accessibility Completeness Consistency Validity (Integrity) Uniqueness Currency Reliability Relevancy Timeliness These elements of data quality, in one way or another, build the foundation for an organization to make the best decisions for its business and better communicate and engage with customers. 1. Accuracy The first piece of criteria for good data quality to consider is accuracy, which verifies an organization's information is correct. The measured value should match the actual, true value, and the data must be error-free. Error-free data should be up-to-date, not redundant, and have no typos. Prioritizing data accuracy means organizations can make more informed decisions, foster stakeholder trust, and achieve better business outcomes. When developing data management strategies, remember the actual value of data lies in its accuracy and ability to represent the real world accurately. The overarching goal should be to increase data accuracy, especially as datasets grow continually. 2. Accessibility Accessible data is obtainable at the time it is needed and by those who need it. Having data readily obtainable with traceable changes allows organizations to enhance transparency, accountability, and efficiency. This data quality characteristic is essential for timely decision-making and effective business operations. Data accessibility is not just available when needed but is also usable. The ability to quickly access data allows businesses to respond promptly to market changes, internal demands, and customer needs. If data is inaccessible, its value diminishes, as delays in obtaining the necessary information can lead to missed opportunities, inefficiencies, and poor decision-making. 3. Completeness Completeness refers to whether all the necessary data is available. For instance, while a customer's first and last name might be crucial for communication, their middle initial might be optional. Comprehensive data lets businesses engage effectively with customers, make informed decisions, and operate efficiently. Completeness is one of the critical data quality characteristics because incomplete information can render data unusable. Imagine sending out mail without the recipient's last name. The mail might not reach the intended address, wasting resources, time, and money, ultimately leading to missed opportunities to connect with customers. Incomplete data can impact business operations, decision-making, and customer engagement. 4. Consistency Consistency is another one of the necessary characteristics of data quality. It means the same information is stored and used across multiple instances to match each other. Consistent data is the percentage of matched values across various records, making accurate and meaningful data analytics essential. Data consistency prevents organizations from using contradictory information that undermines their operations and decision-making processes. Consistent data supports accurate analytics and effective business operations and fosters trust in the information used across the enterprise. 5. Validity (Integrity) Validity is one of the data quality dimensions verifying values align with specific domain requirements and formats. It signifies that data attributes are appropriate and accurate for their intended use, which any organization needs for maintaining data integrity and usability. This fundamental characteristic of data quality makes sure data is fit for its intended purpose. By maintaining high data validity, organizations can enhance the accuracy and reliability of their data for better decision-making and operational efficiency. 6. Uniqueness Uniqueness verifies that each data point is recorded only once in a dataset, eliminating duplication and overlaps. This data quality characteristic maintains the integrity and reliability of data, supporting accurate analysis and effective decision-making. Prioritizing uniqueness improves an organization's data accuracy and reliability, leading to more trustworthy analytics. Implementing thorough data cleansing and deduplication processes allows for keeping unique records, further building upon data governance and compliance efforts. As a result, fostering data uniqueness is key to effective data management and organizational success. 7. Currency Currency directly impacts the relevance and accuracy of the information used for decision-making. Currency refers to how recently the data was collected or updated to reflect the most up-to-date and contemporary reality. Data currency checks that data remains relevant and accurate over time. Focusing on the recency of data collection and updates allows organizations to have high data quality for more accurate insights and better decision-making. Maintaining current data is considered part of the criteria for good data quality, as it drives organizational success in a rapidly changing environment. 8. Reliability Reliability encompasses the degree to which data is factual across various sources and systems. Reliable data means the information used for analysis and decision-making falls within the acceptable values for the specific task or question. Reliable data increases trust, improves operational efficiency, and mitigates risks associated with inaccurate data. Implementing validation rules and maintaining audit trails builds data reliability. Ultimately, reliable data provides a solid foundation of accurate and trustworthy information. 9. Relevancy Relevance is one of the elements of data quality determining whether collected data serves a meaningful purpose. It pertains to whether the data collected is necessary and helpful in achieving specific business goals and objectives. Without relevancy, data collection efforts can become wasteful and unproductive. Relevant data collection efforts are purposeful and align with business goals. Data relevancy allows organizations to use resources more efficiently, extract valuable insights, and conduct focused analyses. Implementing practices to define goals, evaluate the necessity of data, and align data with applications creates relevant data. 10. Timeliness Timeliness refers to how current and up-to-date the information is. In an era where information constantly evolves, timeliness can be considered one of the mandatory data quality dimensions. Organizations can gain a competitive edge by designing timely data collection, storage, and updates and making informed decisions based on the most recent information available. Data timeliness contributes to organizational success by enacting data quality management systems supporting rapid data processing and frequent updates. Maintaining data quality High-quality data is essential for a business's success, and incorporating these characteristics of data quality in your data management plan will save you time, money, and resources in the long term. Developing the criteria for good data quality in your organization helps you avoid relying on invalid or incomplete information. Experian’s data quality management tools can help you with your data quality platform. Contact us today to get started with cleansing and maintaining your data. Connect with a data quality expert today:

What’s happening in the world of contact data verification? Why is it important? And what should you be looking out for? When address validation first became a product, the focus was on increasing the effectiveness of direct mail campaigns and ensuring delivery of important account notifications and legal documents. But times have changed and while these are still important reasons for employing an address validation solution, there are now even more reasons and benefits. Address validation enables eCommerce With the advent and rapid growth of eCommerce, the capacity of carrier services to deliver packages within a short timespan became stretched and the services offered were too limited to meet all needs. This created the need for third-party logistics companies and greater use of traditional business carriers, such as UPS and FedEx, for residential deliveries. In turn, these alternatives often charge fees returning undeliverable mail or to correct inaccurate mailing addresses. In recent years, these fees have become substantial, and vendors are turning to address validation to help reduce or avoid such charges. Originally viewed as a distant competitor for brick-and-mortar retailers, eCommerce has since become a vital component for omnichannel retailers hoping to not only gain business growth from their eCommerce channel but also to drive traffic to their stores via “buy online and pickup in store” and “curbside pickup” options. Digital acceleration, as evidenced through the growth of eCommerce, has reduced the timescale during which it’s acceptable to verify the accuracy of information, from days or weeks to seconds. You need the correct consumer contact data right now. Verifying the reliability of consumer contact data regularly used to be entirely adequate. Now, with consumers expecting to be able to make substantial purchases or open accounts online within minutes, the need for real-time validation and authentication has also become important. The bottom line: Implement an easy-to-use address verification software that quickly identify errors at the point of capture. Make sure the solution can also validate and format stored addresses to meet the standard address format. Not only will the fix and verify an address that a customer enters but you will also see a significant ROI on eCommerce, direct mail campaigns, and more. Reliable address data results in high ROI In today’s world, address validation software is even more valuable to digital acceleration. This helps you see higher ROI on eCommerce deliveries and can also be used to better understand who your customers are, even in a digital market. Address verification is a key component of identity matching—a way to ensure that enrichment data, such as demographic information, credit/income bracket, and lifestyle segment data, is correctly assigned. Data enrichment gives you a sense of what they really care about. Pair that with the right customer address, you have consumer psychographics and demographics to properly target them through preferred channels, like eCommerce, and deliver a personalized customer experience through marketing efforts. Of course, having accurate customer data also makes the marketing and eCommerce budget go further for all the reasons we listed above and way more. Here’s an example: Without accurate customer data—contact and enriched information—special offers designed to acquire new loyalty program members or first-time subscription service users can be taken advantage of by existing customers signing up under different names, family member names, or variations of their own name. A quick check of who’s already signed up at their address can help reduce the occurrence and also make sure that you are targeting your customer base with a message that will resonate. Reasons why you want address verification Accurate address data is the foundation of efficient operations and positive customer experiences. As organizations increasingly rely on digital channels, validating addresses at the point of capture helps ensure customer information is correct from the start. Address verification can help organizations: Reduce delivery failures by ensuring packages, statements and important communications reach the intended recipient the first time. Lower operational costs by minimizing returned mail, address correction fees and the time spent resolving delivery issues. Support a seamless customer experience by preventing delays caused by incorrect or incomplete address information during checkout, registration or account creation. Improve marketing performance by ensuring campaigns reach the right audience and reducing wasted spend on undeliverable mail. Strengthen customer data quality by standardizing address information and creating more accurate customer records across systems. Enable better business decisions by providing reliable location data that supports customer analytics, demand forecasting, territory planning and service optimization. Without address verification, organizations may experience: Increased returned mail and undeliverable shipments. Higher shipping and address correction costs. Duplicate or incomplete customer records. Delayed customer communications and fulfillment. Reduced marketing effectiveness due to inaccurate contact data. Poor customer experiences that can impact trust and loyalty. By validating addresses in real time and maintaining accurate records over time, organizations can improve efficiency, reduce unnecessary costs and build a stronger foundation for customer engagement. How Experian can help Maintaining accurate address data is essential for improving operational efficiency, reducing delivery issues and creating better customer experiences. Experian's address verification solutions help organizations validate, standardize and enrich address information at the point of capture and across existing databases. Whether you're verifying addresses in real time during online transactions or cleansing large volumes of existing customer records, Experian's solutions help improve data quality, reduce costly errors and support more reliable business processes. By ensuring address information is accurate and complete, organizations can streamline deliveries, improve customer communications and make more confident, data-driven decisions. Contact us to learn more:

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