Data analytics application development introduces many challenges including: new roles not in traditional software engineering practices – e.g. data scientists and data engineers; use of sophisticated machine learning (ML) model-based approaches replacing many programming tasks; uncertainty inherent in the models; interfacing with models to fulfill software functionalities; as well as deploying models at scale and undergo rapid evolution, as business goals change and new data sources become available. We describe our Big Data Analytics Modeling Languages (BiDaML) toolset to bring all stakeholders around one tool to specify, model and document big data applications. We report on our experience applying BiDaML to three real-world large-scale applications. Our approach successfully supports complex data analytics application development in industrial settings.