The current evolution into Internet of Things is leading to the permanent connectivity between humans and their surrounding things, generating a vast volume and variety of data, usually at high velocity. Although a significant progress has been made, mainly in what concerns integrating data warehouse architectures with big data analytics for real-time processing of semi-structured and unstructured data types, several challenges still remain on providing data governance, data quality and data stewardship. This workshop aims at bringing together researchers from different scientific communities working on areas of Big Data warehousing and Big Data analytics in order to examine how the fundamental principles of traditional EDW joined with Big Data technologies will build the Big Data systems of tomorrow.

Authors are encouraged to submit both theoretical and applied papers on their research in Big Data warehousing and analytics. Suggested topics of interest include, but are not restricted to:
• Big Multidimensional Data
• Big Data Warehouses Modeling
• Big Data Warehouses Implementation
• Big Data Analytics and Visualization
• Big Data On-Line Analytical Processing
• Big Real-Time Data Warehousing
• Big Data Mining/Large-Scale Text and Graph Mining
• Big Spatio-Temporal Data Warehousing
• Big Spatio-Temporal Analytics and Visualization
• Big Data Applications


LNCS Papers will be published as part of the conference proceedings by Springer in the Lecture Notes in Computer Science (LNCS) Series