BI4MASSES
Business Intelligence for the Masses
| Coordinatore | Ozyegin University
Organization address
address: NISANTEPE MAH ORMAN SOK 13 contact info |
| Nazionalità Coordinatore | Turkey [TR] |
| Totale costo | 100˙000 € |
| EC contributo | 100˙000 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2009-RG |
| Funding Scheme | MC-IRG |
| Anno di inizio | 2010 |
| Periodo (anno-mese-giorno) | 2010-07-02 - 2014-07-01 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
Ozyegin University
Organization address
address: NISANTEPE MAH ORMAN SOK 13 contact info |
TR (ALEMDAG CEKMEKOY ISTANBUL) | coordinator | 100˙000.00 |
Mappa
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Obiettivo del progetto (Objective)
'Whoever can process more data faster and turn it into useful information quickly becomes a global leader in today’s digital world. There may be millions of personal computers and thousands of supercomputers in the world, but the analysis of both stored and streaming data keeps lagging due to the lack of online, easy-to-use, and semi-automated data processing and analytics software. USA has made breakthrough progress over the last decade both academically and industrially in the KDE field and there is ongoing work towards realizing the so called “Business Intelligence (BI) for the Masses” vision. Other recent news suggest that India and China may also be making significant progress in the same direction. Therefore, it is crucial for Europe to boost investments in novel CC-based KDE technologies. This objective of this proposal is to design and implement an on-demand, integrated, and scalable cloud analytics technology with a high potential for wide-scale use and impact. Numerous databases, data processing engines have been developed in the past, but the state-of-the-art in this domain can simply be summarized as “enterprise-class desktop applications”. The proposed project will consist of four major phases each taking about 1 year and each consisting of four parts. PHASE1 is the design and implementation of a scalable distributed cloud infrastructure as a service. It is followed in PHASE2 by the design and implementation of the data mining and reporting service over the infrastructure developed in PHASE1. In PHASE3, we focus on developing the real-time data stream and complex event processing service. Finally, in PHASE4 we will develop and demonstrate the intelligent applications using the platform services developed in phases 2 and 3. We also plan to use open-source software methodologies and tools and provide open access to each architectural layer through web services.'
Introduzione (Teaser)
An EU team developed scalable systems for analysing cloud-stored data. The real-time applications were successfully demonstrated at several large companies, where they were used for network analysis and sensor validation.
Descrizione progetto (Article)
A vast amount of information is stored in online cloud systems, which may mean competitive advantage for any business able to analyse it. A lack of suitable software currently makes such analysis difficult, thus Europe may benefit from investing in such technologies.
The EU-funded 'Business intelligence for the masses' (BI4MASSES) project aimed to design and implement scalable cloud analytics software. The undertaking consisted of four phases: introduction of a distributed cloud infrastructure service, data mining and reporting, real-time stream processing and development of applications. The project ran between mid-2010 and mid-2014.
Team members first designed and implemented a suitable cloud infrastructure onto which several distributed systems data processing tools were installed. Next came design and implementation of a data mining and reporting service, using open-source tools.
Although the work led to several publications, the prototypes could not be expanded to support millions of users as intended. The reason was lack of a sustainable business model, which the project's Principal Investigator and one student overcame by establishing a separate company.
Subsequently, the project developed a prototype real-time data stream and complex event processing service. Lastly, the project created and demonstrated intelligent applications based on the previously developed platform services. The applications were delivered to a variety of large companies; the tools were applied to analysing various kinds of networking logs and validating sensor data.
The project yielded five Masters theses. Three PhD students were continuing studies at the time of the project's closure.
BI4MASSES yielded new software tools for analysing cloud data for business applications.