1) Streaming analytics platforms for IoT need to focus on ingesting data from various sources, processing data in real-time, analyzing data, responding to events, and visualizing data. 2) Key areas for building such a platform include using a common abstraction layer, minimizing latency, integrating static and real-time data using lambda architecture, scaling out linearly, enabling rapid application development, and providing data visualization. 3) An example use case of a connected car generates large amounts of data that can be used for various purposes through a streaming analytics platform like predictive maintenance and customized experiences.