4.11.17
Melissa, a leading provider of global data quality and identity verification solutions, today launched Contact Zone as a comprehensive customer data management platform. Contact Zone is optimized for organizations that want to make trusted data available across the enterprise through the marriage of Pentaho Data Integration (PDI) and Melissa global data verification and enrichment tools. By combining powerful extraction, transformation, and loading (ETL) capabilities with seamless data cleansing and enrichment functionality, data stewards can readily gain a single customer view, break down information silos, improve data quality, and develop CRM and marketing strategies that boost revenue.
“The strongest customer relationships are built on clean, reliable data – updated, enhanced, and managed effectively as part of a long term business strategy,” said Bud Walker, vice president, enterprise sales and strategy, Melissa. “Contact Zone’s extensive data cleansing and enrichment capabilities enable data stewards to capitalize on this approach in a single platform. Unstructured data becomes trusted, actionable information, fueling better decisions and more productive operations that treat every customer as an audience of one.”
Contact Zone offers an intuitive, graphical, drag-and-drop design environment. Data managers can visually design data transformations, apply standards, and cleanse and enrich Big Data stores for easy reporting, analysis, and migration to the data warehouse. With hundreds of integrated database connectors, Contact Zone offers ETL capabilities for all types of relational and Big Data. Data can be easily imported from different sources, and exported as clean, enhanced data ready for meaningful and accurate enterprise analytics.
Contact Zone offers a proven, scalable, standards-based architecture; its full spectrum of data quality operations including profiling, generalized cleansing, address/name/phone/email verification, global ID verification, IP and geo-location, deduping and golden records, can be executed via Hadoop or the cloud as either batch or real-time processes.
