A number of IoT platform offerings have recently entered the market. Leading IoT Platforms as a Service include Oracle IoT Cloud, Amazon IoT, IBM Watson IoT, Salesforce IoT, Microsoft Azure IoT, and more. By definition, these solutions do not exist on an island. They need to collect data in a myriad of formats from hundreds or thousands of sensors; upload, cleanse and transform the data; maintain data in persistent storage; and finally deliver value by applying machine learning and analytics to drive informed decisions and actions, by humans and machines. Emphasis will be on key capabilities and common analytics workfows. We will address common questions including: – What analytics and machine learning capabilities should we expect from our IoT PaaS providers? – How do we integrate IoT data in the cloud with on-premise enterprise transaction systems? – How do we effectively manage machine learning models and iterative workflows? – How do we transition from an on-premise operational data store or data warehouse to cloud-based analytics? – What new capabilities do we see on IoT PaaS horizon?