Business intelligence for the people
Business intelligence (BI) technologies such as data warehousing and On-Line Analytical Processing (OLAP) are major decision-support tools that used to necessitate heavy financial and human investment. Yet, there now exist numerous free BI suites including proprietary, open source and/or cloud solutions. However, proprietary software mostly focus on dashboards and visualization and all have limited functionality, e.g., lack of efficient data integration from disparate sources. Moreover, although some open source software do handle OLAP exploration, they are still technically out of the reach of small companies, non-governmental organizations, researchers, independents such as journalists or makers, and active citizens, whom we particularly target in this project. Finally, the cloud BI trend crosses with the growing demand for collaborative tools that enable users to mashup private, self and open data, perform joint analytics, annotate figures or reports and communicate through social networks. Current answers to this global demand remain below expectations, mostly pertaining to sharing analysis results online.
The aim of BI4people is to bring the power of OLAP interactive analysis to the largest possible audience, by implementing the data warehousing process in software-as-a-service mode, from multisource, heterogeneous data (typically under the form of tables from spreadsheets, textual and semi-structured documents, or the Web) integration to very simple OLAP-like analysis and data visualization (dataviz). To achieve this goal, the BI service must implement privacy by design, be autonomous, extremely simple, user-friendly and intelligible (IT and BI jargon proscribed!). In this framework, classical data warehousing stages still apply, but must be fully automated. To the best of our knowledge, BI4people would be the first platform to achieve this goal, as similar projects relate to automating machine learning processes instead. Moreover, the software prototype we plan as the main deliverable of the project will implement privacy by design in all steps, allow collaborative analyses and be effectively intelligible to users. We indeed stress the importance of dataviz appropriation by users, which involves an interdisciplinary collaboration between computer and information and communication sciences.
Global process