Evidence Based Big Data Benchmarking to Improve Business Performance

Objective

Organisations rely on evidence from the Benchmarking domain to provide answers to how their processes are performing. There is extensive information on how and why to perform technical benchmarks for the specific management and analytics processes, but there is a lack of objective, evidence-based methods to measure the correlation between Big Data Technology (BDT) benchmarks and an organisation’s business benchmarks and demonstrate return on investment. When more than one benchmarking tool exists for a given need, there is even less evidence as to how these tools compare to each other, and how the results can affect their business objectives. At the heart of the DataBench project is the goal to design a benchmarking process helping European organizations developing BDT to reach for excellence and constantly improve their performance, by measuring their technology development activity against parameters of high business relevance. DataBench will investigate existing Big Data benchmarking tools and projects, identify the main gaps, provide a robust set of metrics to compare technical results coming from those tools. It will provide a framework to associate those technical results with the economic processes that are imperative to a company. It will provide a robust set of benchmarks to assess which tools respond best and provide the most pertinent information for organisation’s economic planning and respond to their current and emerging industrial needs. It will provide a software tool which the industrial and research community users can leverage to do this evaluation. DataBench will interact with ICT14 and 15 projects to give access to this tool and framework to leverage the Big Data benchmarking investment so far carried out in the benchmarking community, contributing to the success of the BDV-PPP. The project envisions continuous interaction with the leading BDT suppliers and industrial user communities, and has a strong relationship with the BDV cPPP.

Fields of science

• natural sciences › computer and information sciences › data science › big data
• social sciences › economics and business

Programme(s)

• H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)

Topic(s)

• ICT-17-2016-2017 - Big data PPP: Support, industrial skills, benchmarking and evaluation

Call for proposal

H2020-ICT-2017-1
See other projects for this call

Funding Scheme

RIA - Research and Innovation action

Coordinator

IDC ITALIA SRL

Address

Viale Monza 14
20127 Milano
Italy

Activity type

Private for-profit entities (excluding Higher or Secondary Education Establishments)

EU contribution

€ 685 624,73

Participants (7)

ATOS SPAIN SA

Spain

EU contribution

€ 438 162,53

Address

Calle De Albarracin 25
28037 Madrid

Activity type

Private for-profit entities (excluding Higher or Secondary Education Establishments)

POLITECNICO DI MILANO

Italy

EU contribution

€ 340 850,24

Address

Piazza Leonardo Da Vinci 32
20133 Milano

Activity type

Higher or Secondary Education Establishments

STIFTELSEN SINTEF

Participation ended

Norway

EU contribution

€ 0

Address

Strindveien 4
7034 Trondheim

Activity type

Research Organisations

INSTITUT JOZEF STEFAN

Slovenia

EU contribution

€ 288 690

Address

Jamova 39
1000 Ljubljana

Activity type

Research Organisations

JOHANN WOLFGANG GOETHE-UNIVERSITAET FRANKFURT AM MAIN

Germany

EU contribution

€ 89 783,75

Address

Theodor W Adorno Platz 1
60323 Frankfurt Am Main

Activity type

Higher or Secondary Education Establishments

SINTEF AS

Norway

EU contribution

€ 326 752,50

Address

Strindvegen 4
7034 Trondheim

Activity type

Research Organisations

LEAD CONSULT LTD

Bulgaria

EU contribution

€ 71 125

Address

Shejnovo Str. 11
4000 Plovdiv

Activity type

Private for-profit entities (excluding Higher or Secondary Education Establishments)