DistillerSR Reviews

Looking for fast, easy solutions to protect your entire data lifecycle? Look no further. Melissa’s Web APIs offer a range of capabilities to keep your customer data clean, verified, and enriched, powered by AI-driven reference data. Our solutions work throughout the entire data lifecycle – whether in real time, at point of entry or in batch. • Global Address: Verify & standardize addresses in 240+ countries & territories with postal authority certified coding & premise-level geocoding. • Global Email: Verify email mailboxes, syntax, spelling & domains in real time to ensure they are deliverable. • Global Name: Verify, standardize & parse person & business names with intelligent recognition of millions of first & last names. • Global Phone: Verify phone as active, identify line type, & return geographic details, dominant language & carrier for 200+ countries. • Global IP Locator: Gain a geolocation of an IP address with lat & long, proxy info, city, region & country. • Property (U.S. & Canada): Return comprehensive property & mortgage data for 140+ million U.S. properties. • Personator (U.S. & Canada): USPS® CASS/DPV certified address checking, name parsing & genderizing, phone & email verification are all easily performed with this API. With these tools at your disposal, managing and protecting your customer data has never been easier.

Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.