Data Economy is an integral part of the Digital Single Market strategy of the European Commission, and as such, it is considered as an essential resource for growth, competitiveness, innovation, job creation and societal progress in general. It is however widely acknowledged by the industry that many companies continue to struggle to turn opportunity from big data into realized gains. There is little actual knowledge on how organisations translate the potential of big data into actual economic and social value.
Moreover, relevant to I-BiDaaS is the debate on algorithmic and human-based intelligence and in particular the acknowledgement that when processing and interpreting data, human actors can be influenced, for example, by time constraints and scepticism with regard to relying on data; team compositions; visualizations of input and output; relational versus analytic and evidence-based mind sets, and historical insights. To mitigate such influences, scholars and practitioners have begun to explore the potentials of algorithms that are able to process big data at ever-increasing speeds.
Within this logic the I-BiDaaS consortium reflected on the 4 steps proposed by the European Commission in order to leverage on the potential of Big Data as well as the motivation behind the targeted call under H2020 -ICT-2016-2017 which was to develop technologies that would increase the efficiency of all EU companies and organisations that need to manage vast and complex amounts of data and in particular the competitiveness of EU enterprises. In this context, the emphasis is on rigorously measured increases in performance in data processing at a very large scale.
In this respect, I-BiDaaS is expected to produce services and tools that aim at enhancing big data processing performance for both non-IT users (Comprehensive multiple option user interface, advanced visualizations, fabricating high-quality Big Data for testing) and for IT- users/developers (programming interfaces; Sequential programming paradigm; Open source software repository for Big Data processing tasks).
These tools are expected to increase performance in three levels:
1. the speed of data analysis procedures;
2. the usability and applicability of big data analytics tools and processes;
3. the amount of data that can be processed.
The proposed solutions will be made available through existing incubators thus enabling SMEs, start-ups and entrepreneurs to exploit them and accelerate their development further. In a nutshell, I-BiDaaS will deliver a full array of big data business analytics solutions for structured, unstructured, noisy data for companies in multiple industries (finance, telecom and automotive) that are more accessible, cost-effective and employee-empowering than existing solutions, which gives companies the confidence to deploy Big Data Self-Service solutions across the organisation, from consumer-facing employees with little IT experience or expertise to top.