Remove or correct anomalies
AI improves data quality by reducing human error. When data is entered manually, there is always the potential for mistakes, particularly duplicate entries, typos, and incomplete data. Even the smallest act of carelessness can affect the quality of data. With AI-enabled systems, these mistakes can be removed or corrected. Not only does AI correct the error automatically, but it can also be programmed to scan old data sets periodically to ensure quality is clean.
Identify and learn from patterns
Another way AI improves data quality by identifying patterns that would be difficult for humans to spot. For example, let’s say you are looking at a dataset of customer purchase history. It would be very time-consuming for a human to go through hundreds, if not thousands, of entries to find all the instances where a customer purchased a certain item after another specific item. However, an AI can quickly identify these patterns and provide you with valuable insights.
AI boosts efficiency in data collection and data management, making it less likely for you to have to constantly go back and check the quality of your data manually. An AI-enabled system detects duplicates automatically, ensures data is clean, predicts data, and identifies anomalies. AI-powered systems also work best with third-party data collection, allowing you to have data that increase informed decision-making.
Over time, datasets can become cluttered with outdated or irrelevant information. This can make it difficult to find the data you need or make accurate decisions based on the data. However, AI can help you clean up your dataset and remove any unnecessary information. This will leave you with a more streamlined dataset that is easier to work with.
Formatting your records, so they follow consistent data helps create consistency. Consistency in formats such as address formats, dates, abbreviations, and so on helps lead to cleaner data and reduces the risk of duplicates, inaccuracies, missing elements, and typos. AI-powered systems perform better when there is data standardization. And when it is programmed by defining standards, it ensures that all stored data conforms with that defined standard. AI can also process all old data and apply the new benchmarks and metrics across the entire data set.
Leverage technologies such as AI to avoid the consequences of poor-quality data. At RunnerEDQ, we know how important it is for organizations to maintain high-quality contact data. Our solutions were designed to format, standardize, and verify addresses to ensure your alumni and donor records are always updated. We also enhance contact information to include email, phone, and social media handles. Because many of your alumni may have moved or work overseas, we also format and validate international addresses. To learn more, contact us.