BI4MASSES

Business Intelligence for the Masses

 Coordinatore Ozyegin University 

 Organization address address: NISANTEPE MAH ORMAN SOK 13
city: ALEMDAG CEKMEKOY ISTANBUL
postcode: 34794

contact info
Titolo: Dr.
Nome: Nilay
Cognome: Papila
Email: send email
Telefono: +90 216 564 95 68
Fax: +90 216 564 90 57

 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

# participant  country  role  EC contrib. [€] 
1    Ozyegin University

 Organization address address: NISANTEPE MAH ORMAN SOK 13
city: ALEMDAG CEKMEKOY ISTANBUL
postcode: 34794

contact info
Titolo: Dr.
Nome: Nilay
Cognome: Papila
Email: send email
Telefono: +90 216 564 95 68
Fax: +90 216 564 90 57

TR (ALEMDAG CEKMEKOY ISTANBUL) coordinator 100˙000.00

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

data    kde    companies    mid    stream    tools    analysing    services    suitable    scalable    technologies    service    stored    distributed    demonstrated    software    cloud    source    team    bi    masses    reporting    intelligent    phase    intelligence    analytics    business    event    sensor    yielded    online    platform    mining    progress    real    infrastructure    lack    world    millions    time    phases   

 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.

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