Quality analysis of business data provides competitive advantages. However, comprehensive, and timely data discovery to feed analyses is hard. It can involve manually tagging data, ineffective collaboration, and data sensitivity. Consequently, enterprises lose analyst productivity, make decisions on inadequate analyses, and delay complying with regulations. Join us to learn how metadata automation, built-in collaboration, and open and customizable architecture allows organizations to use trusted data to become more collaborative and agile.