In the past few years, many organizations in all domains have discovered that – to become or remain competitive – they have to deal with business cases where the volume of data reaches terabytes and even petabytes. As the volume of data keeps growing, the datatypes to be considered have also become much richer than before. Many IT companies propose to their customers to manage Big Data challenges using a mix of technologies going from NoSQL ("notonlySQL") databases like Cassandra or HBase, data preparation utilities like Paxata, and distributed, parallel computing systems like Hadoop or Stark. However, one of the main obstacles forbidding the widespread adoption of big data approaches in many businesses and enterprises is the lack of competences. In particular, this scenario substantially limits the market for Big Data analytics for non IT-savvy organizations and SMEs. An increasing request is therefore posed on solutions for Big Data Analytics as a service, which will support customers lacking Big Data expertise in configuring and managing their analytics.
The workshop seeks submissions from both academia and industry presenting novel research in the context of big data analytics as a service, presenting theoretical and practical algorithms, techniques, and architecture for big data analytics management.