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In recent years, new challenges have emerged in the automotive sector, particularly in the ADAS/AD domain. The development and testing of such functionality require not only efficient processing and analysis of a rapidly growing amount of recorded vehicle data, but also the ability to deal with a diverse set of new sensor and data types. With its ADAS/AD Big Data & Analytics Platform, AVL addresses these challenges and of-fers a solution that enables highly efficient and scalable search, visualization and anal-ysis of large data sets in an integrated way. A key aspect here is the abstraction of the involved big data mechanisms, since typical users are domain but not big data experts. Additionally, by following standard formats such as Open Simulation Interface (OSI), the ADAS/AD Big Data & Analytics Platform is also broadly applicable. In order to demonstrate the benefits of our platform, we show how it can be applied to logically describe, identify and analyze complex and custom driving scenarios and how tech-nical and legal requirements, such as on an automatically commanded steering function, can be efficiently verified on a large number of test drives.