I-BiDaaS – Industrial-driven Big Data as a self-service solution

Faculty of Sciences at the University of Novi Sad, Serbia, participates as a project partner in the European Union’s H2020 research and innovation project I-BiDaaS – Industrial-driven Big Data as a self-service solution (2018-2020). The I-BiDaaS project includes 13 partner institutions overall, is coordinated by FORTH, Heraklion, Greece, and proposes an end-to-end solution for Big Data as a self-service. See also I-BiDaaS at the website (http://ibidaas.eu/) and on twitter (https://twitter.com/Ibidaas)dusan1

Organizations leverage data pools to drive value, while it is variety, not volume or velocity, which drives big-data investments. The convergence of internet of things (IoT), cloud, and big data, create new opportunities for self-service analytics towards a complete big data analytics paradigm. Human and machine created data are being aggregated, transforming our economy and society. 2016 was a landmark year for big data with more organizations storing, processing, and extracting value, from data of all forms and sizes. In 2017, systems that support large volumes of both structured and unstructured data continued to rise. The market will demand platforms that help data custodians govern and secure big data while empowering end users to analyse it. These systems will mature to operate well inside of enterprise IT [1]. The trends above lead us to one of the main challenges of the data economy [2]. To face these challenges, companies call upon expert analysts and consultants to assist them. However, a self-service solution will be transformative for organizations; it will empower their employees with the right knowledge, and give the true decision-makers the insights they need to make the right decisions. It will shift the power balance within an organization, increase efficiency, reduce costs, improve employee empowerment, and increase profitability.

I-BiDaaS aims to empower users to easily utilize and interact with big data technologies, by designing, building, and demonstrating, a unified solution t
hat: significantly increases the speed of data analysis while coping with the rate of data asset growth, and facilitates cross-domain data-flow towards a thriving data-driven EU economy.

I-BiDaaS will achieve its goals following a methodical approach. As a first step, it has guaranteed access to real-world industry big data. I-BiDaaS will pdusan2roceed with breaking intrer and intra-sectorial data-silos, and support data sharing, exchange, and interoperability. Having done so, it will support methodical big data experimentation by putting in place a safe data processing environment. To foster experimentation, I-BiDaaS will develop data processing tools and techniques applicable in real-world settings. Project’s solution will be tangibly validated by three real-world, industry-lead experiments, in the domains of banking, manufacturing, and telecommunications. The solution will help increase the efficiency and competitiveness of EU companies.

The I-BiDaaS project has received funding from the European Union’s Horizon 2020 Research and Innovation program under grant agreement No 780787.

[1] Top 10 Big Data Trends (2017, April 03) https://www.tableau.com/resource/top-10-big-data-trends-2017, (accessed March 30, 2018).
[2] Self-Service Analytics. (2017, January 03) 
http://www.gartner.com/it-glossary/self-service-analytics, (accessed March 30, 2018).

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