Medical studies have shown that physiological data streams have a lot of potential to reveal early signs of the onset of critical conditions within the pediatric population. Traditional data warehouses provide analysts with fast and easy access to data gathered from operational data sources to support decision making. However Traditional data warehouses have their own limitation with frequency of extraction from data sources. Traditional data warehouses do not support real time analysis of streaming data such as physiological data. Big data analytics uses analytical techniques to process big data with the help of data storage, analysis and visualization technologies. Within healthcare domain Big data analytics can be used to identify previously unnoticed patterns in patients physiological data streams. Cloud computing infrastructures can serve as an effective platform to address both the computational and data storage needs of big data analytics applications. Cloud based analytics-as-a-service tools provide real-time Clinical Decision Support Systems (CDSS) capabilities.