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The adoption of data science brings vast benefits to Small and Medium-sized Enterprises (SMEs) including business productivity, economic growth, innovation and job creation. Data science can support SMEs to optimise production processes, anticipate customers' needs, predict machinery failures and deliver efficient smart services. Businesses can also harness the power of artificial intelligence (AI) and big data, and the smart use of digital technologies to enhance productivity and performance, paving the way for innovation. However, integrating data science decisions into an SME requires both skills and IT investments. In most cases, such expenses are beyond the means of SMEs due to their limited resources and restricted access to financing. This paper presents trends and challenges towards effective data-driven decision making for organisations based on a 3-year long study which covered more than 85 UK SMEs, mostly from the West Midlands region of England. In particular, this study attempts to find answers to several key research questions around data science and AI adoption among UK SMEs, and the advantages of digitalisation and data-driven decision making, as well as the challenges hindering their effective utilisation of these technologies. We also present two case studies that demonstrate the potential of digitisation and data science, and use these as examples to unveil challenges and showcase the wealth of currently available opportunities for SMEs. [ABSTRACT FROM AUTHOR]

This paper presents a comparative analysis of the feasibility studies submitted by six UK cities (London, Birmingham, Manchester, Glasgow, Bristol and Milton Keynes). The datasets were collected during the period of February–March 2017 by exploring their Open Data resources, common visions of their smart programmes and the themes of their projects. The aim of this work is to raise awareness and access of the existing data resources, encourage alignment of data collection and curation among projects with compatible objectives in different cities and to identify the gaps in coverage that are hampering achievement of the cities' visions. In this research, we distinguish between stored datasets that are accessible via data hubs, and live data that are only accessible via application programming interfaces in real time. Given that our findings are purely based on stored Open Data, we conclude that the Smart City dream will be only achieved in reality, where those involved in Smart Cities-related projects co-operate and share both experiences and resources in order to maximize progress towards the common goal but to minimize duplication of efforts and repetition of the same mistakes. [ABSTRACT FROM AUTHOR]