Seamless Data Quality Powers Actionable Intelligence from Customer Data
Melissa, a leading provider of global contact data quality and identity verification solutions, announced it will demonstrate its comprehensive suite of Big Data Quality tools and services at Chief Data & Analytics Officer Singapore, July 23-24, 2019. Melissa’s Big Data Quality tools prevent incorrect, incomplete, duplicated, or outdated data from entering enterprise systems, ensuring analytics are fueled with the actionable intelligence necessary for authoritative results.
By partnering with leading data integration providers, Melissa enables simplified data verification and identity verification, and serves as a central operational hub for all federated customer and identity data. The company’s tools work seamlessly in the ETL process to empower businesses to ingest structured and unstructured large volume data and improve operations in record time by interfacing with legacy repositories, Big Data lakes, and real-time streams, or assisting in migration to modern infrastructure.
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Melissa recognizes that data officers face volume, variety, and velocity of data factors that create challenges in storing, maintaining, and analyzing customer data. Seamless data quality makes a difference by enabling a sustainable analytics strategy, preventing the GIGO (Garbage In, Garbage Out) that gets in the way of valuable analytics.
“Just because a business has access to a lot of data does not mean it has established authoritative, useful intelligence,” said Edmund Ng, Regional Sales Director Asia Pacific, Melissa. “Authoritative customer data needs to be merged with Big Data to derive what customers want to buy, what they have already purchased, and their sentiments toward specific products. These insights are critical in driving smart decisions in marketing and promotions.”