Artificial intelligence and one of its promising areas, machine learning, have been widely used by the research community to turn massive, diverse, and even heterogeneous health care data sources into high quality facts and knowledge, providing leading capabilities to robust pattern discovery. However, the application of machine learning strategies on big and complex medical datasets is computationally expensive, and it consumes a very large amount of logical and physical resources, such as data storage, CPU, and memory. Additionally, and from the implementation perspective, most big data machine learning algorithms are complex, and their implementations are available for few environments. These operational restrictions cause various difficulties for utilization of big data analytics, and even more, they create challenges to establish novel experiments and develop new research ideas. 

Sophisticated big data analytics-as-a-Service platforms for efficient data analyses is becoming more valuable as the amount of data generated daily in the health care literature exceeds the boundaries of normal processing capabilities. The objective of the bigdas@KDD2017 is to provide a professional forum for data scientists, researchers, and engineers across the world to present their latest research findings, innovations, and developments in turning big data health care analytics into fast, easy-to-use, scalable, and highly available services over the Internet. This workshop is aimed at data science practitioners working at the intersection of big data machine learning, Software as a Service (SaaS) platforms, Internet of Things (IoT), and health informatics. It will highlight current trends and insights for the future of health data analytics, which is bigger and smarter. 

The first workshop on Big data analytics-as-a-Service: Architecture, Algorithms, and Applications in Health Informatics is taking place on August 14, 2017 (in conjunction with KDD 2017) in Halifax, Nova Scotia, Canada. The workshop will consist of a combination of invited keynote speakers, panel discussion, and paper/poster presentations. We allocate significant time for open discussions on sharing best practices and future directions.