Connecting Data

Connecting data is a joint study between the Royal Academy of Engineering and the IET, which explores the importance of big data, data analytics and improved connectivity to engineering-based firms. The study aims to map the opportunities and challenges that industry has identified from connecting data in the digital economy now and into the future (2015-2020). We plan to produce a report in autumn 2015.


In January and July 2014, The Royal Academy of Engineering held separate workshops on data analytics and 5G to consider the potential offered by these technologies and related applications. The outcome of the workshops was a wish to explore more deeply the potential economic benefits of both sets of technologies and their potential to help address the major challenges facing the country. Each workshop separately arrived at the conclusion that it should be followed by sector-specific studies or workshops which the examined impact of connected systems. Image of a man holding a mobile device with data signals flowing out of the device  

Data analytics will develop and grow with more connected machines, higher speeds, greater bandwidth and Internet reliability but it was felt that it may be useful to combine topics into one study, demonstrating how they will go hand in hand and how various sectors can ultimately benefit from these ‘enabling technologies’.

A series of workshops focused on the following sectors:

  • Transport
  • Energy and environment
  • Built environment
  • Healthcare
  • Manufacturing
  • Defence and aerospace

Emerging Themes

The workshops have produced some recurring themes that will form the basis of the report. These include:

  • Identifying business cases
  • Privacy and security
  • Quality and integrity of data
  • Lack of skills
  • Interoperability

The report would look to raise the profile of some of the key benefits of data and improved connectivity/connected systems and aim to offer specific recommendations in the realm of making the UK more competitive and connected in data-driven engineering.