Melissa - Verify Addresses & Identities

Today, efficiency is all about automation and machine learning. When it comes to machine learning, the quality of data plays a crucial role in determining the quality of the results. Without good quality data, the effects of machine learning can be detrimental to an organization’s progress. The phrase, “garbage-in, garbage-out” holds true in such scenarios. Data quality has an effect on machine learning, not once but twice- when a predictive model is trained and in making future decisions. Effect of Data Quality on Training Predictive Models Predictive models need data during the training phase. This historical data should ideally meet very high quality standards- it should be standardized, accurate, unique, properly labeled and complete. The data being used should also cover the entire range of input needed to develop the predictive learning model. Thus, when it comes to the data being used for predictive models, one must focus on all the criteria for quality control s...

Rancho Santa Margarita, CALIF – January 8, 2020  –  Melissa , a leading provider of global address, name, email, phone, and identity verification solutions, is celebrating its 35th anniversary with renewed commitment to continued growth and enterprise data quality leadership. The company’s longevity can be attributed to decades of address expertise and deep domain knowledge that builds the foundation for global intelligence – everything from demographic, business, location and identity data. It is this foundation that empowers risk management, data-driven engagement, analytics, insight, and compliance. Read More