Decision-support information systems notably rest on data warehouses and on-line analytical processing (OLAP), two pillars of business intelligence (BI) that are nowadays confronted to new scientific and technological challenges. Traditional data warehouses can indeed handle hundreds of terabytes of data, but hardly manage little-structured or unstructured data such as texts and graphs, nor quickly incoming data, thus inefficiently supporting real-time BI.
In parallel, with the emergence of big data-related technologies and the diffusion of data mining and machine learning algorithms, new perspectives open for analytical and decision-support uses. The proliferation of little-structured or unstructured data, data flows from, e.g., sensors, the Internet of things or social media, coming in huge volumes, is indeed a huge opportunity for BI and sparkles new research areas in data warehousing and OLAP.
Data warehousing and OLAP still operate in various organizations to structure and analyze both legacy and new data. They retain a key role in piloting such organizations (administrations, companies, hospitals…). Then the question is how to preserve their strengths while moving data warehouses and OLAP toward solving big data issues?
Big data bring us into a new scientific and technological era offering architectures and infrastructures (clouds, Hadoop-like computing, NoSQL databases…) that allow better data management and analytics for decision-making. Such an evolution raises new problems that require the design of new approaches for data integration, modeling, querying, analysis, optimization and security, both in traditional and big data warehouses.
Since 2005, the French-speaking conference on data warehousing and OLAP (EDA) has been offering a regular meeting framework to researchers, industrials and users interested in the latest scientific and technological advances in this domain. We call all researchers and experts in this domain to present their work. We particularly encourage young researchers to participate. Submitted papers may be written either in French or in English and must describe original research and applications related to the following topics (non-exhaustive list).