miproBIS 2015 - Business Intelligence Systems

The term Business intelligence (BI) refers to applications and technologies used to gather, provide access to, and analyze data and information about company operations in order to help them to have a more comprehensive knowledge of the factors affecting their business. BI systems usually lean on data warehouses (DWs) to guarantee an easy and quick access to information. More than ten years of research in the data warehousing field paved the way for new applications that goes beyond traditional OLAP analysis and concern real-time, spatiotemporal as well as distributed data. Furthermore, BI research is now dealing with the integration of BI with Corporate Performance Management (CPM), Business Process Management (BPM), Social Business Intelligence, Semantic Web, and Big Data.
Like the previous successful editions, miproBIS 2015 provides an international forum where both researchers and practitioners can share their findings and practical experiences in the field of BI. In particular, besides submissions in traditional DW and OLAP topics, we encourage papers concerning emerging research topics and applications in the DW, OLAP and BI area.
The scope of the conference includes, but is not limited to:
Data warehouse design and schema evolution
Multidimensional modelling and queries
Data warehousing consistency and quality
Online Analytical Processing (OLAP)
Tools for data warehousing and OLAP
Integration of data warehousing and data mining
Metadata management
Integration of Business Process Management (BPM) and Business Intelligence (BI)
Forecasting and simulation in Business Intelligence
Corporate Performance Management (CPM) and Business Intelligence
Balanced scorecards
Decision Support Systems
Active/real-time data warehousing
Data warehousing with unstructured and semi-structured data (e.g. XML)
Data warehousing and industry applications (e.g. ERP, CRM)
Data warehousing in mobile/wireless environments
Biomedical data warehousing
Cloud intelligence
Warehousing stream and sensor data
Temporal, spatial and spatiotemporal data warehouses
Analytics for multimedia data
Social Business Intelligence
Business Intelligence on Social Data
Sentiment Analysis
Semantic Web
Semantic Web & Deep Web in Data Warehouses
Ontologies & Data Warehouses
Big Data
Using MapReduce in Data Warehouses
SQL Vs MapReduce for Analytical Processing
Smart Grid & Data Warehousing