Disparate data sources are a big hurdle to enterprise sales and marketing, supply chain optimization, compliance and risk modeling. Lack of a trusted unified view of customers, suppliers, products and parts affects personalization, analytics, cross selling, recommendations, spend optimization and other core business functions. Unifying this data is challenging, as there are schema and record level variations like typos, missing fields, abbreviations, etc. The scale of data and the variety of systems and formats makes it a tough problem to solve. In this talk, we describe how we are leveraging Elasticsearch and ML over Spark to provide a unified view of mastered customer, suppliers, supplies and other entities. Elastic is a core part of our application, enabling quick access and discovery of mastered records at scale.