This guide focuses on the challenges of data preparation and the value of self-service solutions that empower business users and analysts. It explains how manual data transformation consumes excessive time and introduces errors, and outlines six key requirements for effective self-service data preparation. Topics include access to semi-structured data, automation, governance, data masking, and scalability. The guide demonstrates how organizations can increase efficiency, reduce risk, and improve trust in analytics by enabling repeatable, governed data workflows without relying on specialized IT resources.

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