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Evidence Based Big Data Benchmarking to Improve Business Performance

Periodic Reporting for period 2 - DataBench (Evidence Based Big Data Benchmarking to Improve Business Performance)

Reporting period: 2019-07-01 to 2020-12-31

Driven by well-documented success of internet giants in the mass distribution, retail, and internet marketing sector, most companies now recognize the importance of using Big data Technologies (BDT) to improve their business performance. Unfortunately, given the relative novelty of the technologies most organisations rely on their technology providers not only to help them implement these technologies, but also to assess the performance of the tools they are using. The understanding of the technical underpinnings and their transposition into organizational goals through the results that can be achieved are not strong within the organisations. Even many of the technology providers understand the technical proficiency of their tools but often lack the possibility (or incentive) to benchmark their tools against alternative solutions. There is on one hand, a lack of recognized benchmarking tools to evaluate performance of technologies; and on the other, a disjunct or separation between the tools and the business objectives of the companies where these tools are expected to be implemented.
The overall objective of the DataBench Research and Innovation Action is to provide benchmarks and performance evaluation mechanisms to identify business impact and industrial significance in Big Data Technologies (BDT) benchmarking providing operational support to the BDV PPP and the European Big Data industry. DataBench will provide a tool to quickly guide organisations to find the correct benchmarking process, execute performance measurement and associate the measurements to the business processes which they are expecting BDT to measure and improve. This will help European organisations developing BDT to measure their technology development and compare it to recognized parameters of high business relevance. The expected outcome is the improvement of European companies competitiveness through the selection and implementation of the most advantageous BDT solutions.
To achieve this overall goal DataBench has persued the following six functional objectives:
1 Provide the BDT stakeholder communities with a comprehensive framework to integrate business and technical benchmarking approaches for Big Data Technologies.
2 Perform economic and market analysis to assess the “European economic significance” of benchmarking tools and performance parameters.
3 Evaluate the business impacts of BDT benchmarks of performance parameters of industrial significance.
4 Develop a tool applying methodologies to determine optimal BDT benchmarking approaches.
5 Evaluation of the DataBench Framework and Toolbox in representative industries, data experimentation/integration initiatives (ICT-14) and Large-Scale Pilots (ICT-15).
6 Liaise closely with the Big Data Value Association (BDVA), ICT-14, -15 projects to build consensus and reach out to key industrial communities, to ensure that benchmarking responds to real needs and problems.
According to the project plan all tasks have been performed, and all deliverables have been submitted. As such, all milestones expected for the period, which are described in the section entitled “Milestones” have been achieved. A brief overview includes:
WP1 has investigating and proposing a methodology and model to assess and categorize metrics and KPIs that result from benchmarking initiatives to allow initiatives to be aligned with BDVA Reference Model and the BDVA Strategic Research and Innovation Agenda.
WP 2 has extended the Framework by assessing the processes that are being analysed in the BDT benchmarking initiatives and tracing those activities to the organisational functions that are being monitored and improved. It has surveyed 700 real organisations using BDTs in 11 European countries to illicit real industry needs, as well as a survey of ICT-14 and 15 initiatives to map IDC data regarding the processes currently being benchmarked to use cases across a number of key industries. It has provided a self-assessment tool to allow additional respondents compare their needs with the current database of respondents and receive a detailed report. Work package 2 has taken the first steps to assess and demonstrate which needs and what potential effect can be achieved through benchmarking.
WP 3 has provided an architecture and is developing the DataBench Toolbox able to homogenise existing benchmarking initiatives results synthesizing their utility and providing the Metrics that are used to compute the industrial significance and form the DataBench benchmarks.
WP 4 and 5 assess the Framework and Toolbox. WP4 has assessed the business and industrial relevance using the tool with real industry stakeholders’ technical needs, while WP5 is responsible for the assessment of the accuracy and reliability of the tool’s technical interpretation of the upstream benchmarking initiatives.
WP 6 has created a community essential to gather results from the benchmarking tool for development and testing but also for leveraging the sustainability of the Toolbox by taking it to ICT-14 and 15 projects and the industrial and research communities that can use it. WP6 is disseminating the results of the project through web and social media and through participation at events.
DataBench has provide BDT stakeholder communities with a comprehensive framework to integrate business and technical benchmarking approaches.
DataBench has improved the current state of BDT economic and market analysis has been advanced with a method to analyze the most important objectives companies have for using BDTs and a mapped those to significant vertical sectors and use cases.
DataBench carried out a Survey of 700 organisations that are currently using BDT technologies across 11 member states as well as an interview of the ICT-14 and 15 project.
DataBench has provided the alpha version of the DataBench Toolbox to collect and execute benchmarks.
DataBench has assessed the industrial cases of ICT-14 and ICT-15 projects as well as a set of representative pilots selected from outside the cPPP.
DataBench has provided a mechanism to perform technical evaluation of results when using the DataBench Toolbox for technical KPIs and validation of business metrics based on data measurement including business data, media data, textual data and other significant data sources to assess technical usability, scalability, complexity and relevance of corresponding metrics and data.
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