Big data analytics-A review of data-mining models for small and medium enterprises in the transportation sector <s> Data Management <s> This paper is a review of the literature concerning management development in small firms. It looks at the benefits in terms of growing a small firm and whether the lack of management skills contributes to their failure. In addition, this paper looks at some of the barriers to management development, including the attitudes and characteristics of the entrepreneur, and also looks at learning models that may be appropriate for small firms. The paper also looks at the authors' views on the effectiveness of management development for small firms, the barriers to learning as well as the skills required. Management development programmes are now widely accepted as a means of improving the competitiveness of firms and the economy as a whole. Although management education and training has, in the past, been designed mainly for larger firms, there is a growing awareness of the requirements of small businesses. Government initiatives designed to encourage start-ups and to boost the growth of small firms have emphasized the importance of management development. This review of the literature shows that, on balance, management development programmes are effective for small firms. The main benefits appear to be survival and growth, reduction in failure and improvement in performance. The skills required include leadership and management, developing management systems and techniques and team building. Other skills include planning, delegation and financial management. The paper concludes that there is a need for further research into the effectiveness of management development programmes, the skills required and the barriers to learning in small firms and, also, whether they have an impact on the survival, growth and profitability of small firms. <s> BIB001 </s> Big data analytics-A review of data-mining models for small and medium enterprises in the transportation sector <s> Data Management <s> The amount of data in our world has been exploding, and analyzing large data sets—so-called big data— will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus, according to research by MGI and McKinsey's Business Technology Office. Leaders in every sector will have to grapple with the implications of big data, not just a few data-oriented managers. The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data for the foreseeable future. <s> BIB002 </s> Big data analytics-A review of data-mining models for small and medium enterprises in the transportation sector <s> Data Management <s> Big data is big news, and large companies in all sectors are making significant advances in their customer relations, product selection and development and consequent profitability through using this valuable commodity. Small and medium enterprises (SMEs) have proved themselves to be slow adopters of the new technology of big data analytics and are in danger of being left behind. In Europe, SMEs are a vital part of the economy, and the challenges they encounter need to be addressed as a matter of urgency. This paper identifies barriers to SME uptake of big data analytics and recognises their complex challenge to all stakeholders, including national and international policy makers, IT, business management and data science communities. ::: ::: The paper proposes a big data maturity model for SMEs as a first step towards an SME roadmap to data analytics. It considers the ‘state-of-the-art’ of IT with respect to usability and usefulness for SMEs and discusses how SMEs can overcome the barriers preventing them from adopting existing solutions. The paper then considers management perspectives and the role of maturity models in enhancing and structuring the adoption of data analytics in an organisation. The history of total quality management is reviewed to inform the core aspects of implanting a new paradigm. The paper concludes with recommendations to help SMEs develop their big data capability and enable them to continue as the engines of European industrial and business success. Copyright © 2016 John Wiley & Sons, Ltd. <s> BIB003
• Data security concerns. • Data protection and privacy concerns. In respect of grouping classification, the SMEs nucleus area of concern is mostly in relation to the subject of resources. This is followed by knowledge and data management concerns. It can be deduced that the lack of an in-house data analytics specialist is an implication caused by the insufficient number of available qualified data analytics talent. For instance, in the United States, it is envisaged that by 2018, there will be a shortage of close to 190,000 skilled analytical talent and also a shortfall of 1.5 million analysts and managers with the relevant competency to derive strategic decision(s) from big data analysis BIB002 . A survey carried out amongst recruiters in the UK revealed that up to 57% of the recruiters are facing obscurity in filling up the big data analytics gaps -this is inclusive of the large companies  . The scarcity of qualified data scientists would deter the analytics development scene in the European market  . Given the shortfall of talent supply, it is expected that the existing analytics software, readily available in the market would aid in curbing the impending expertise gap. There are plenty of analytics solutions available in the market. Nonetheless, to find a solution that is both user-friendly and embedded with robust analytical capabilities is scarce. The need for an instinctive user interface is critical in shortening the user learning curve  -allowing faster implementation for the SMEs. As evaluation platforms may tend to be vendor biased; an end user with minimal or zero proficiency in analytics may find it difficult to select a solution with a decent price-performance ratio. With an innumerable number of studies highlighting that financial limitations are the SMEs' major hindrance block  BIB001 , a lower price-performance ratio solution would be more desirable by the SMEs. Finally, yet importantly, data security, protection and privacy are the SMEs' key concerns in the area of data management. Close to 50% of SMEs identified data security and protection as the key barrier to big data analytics -in a worldwide survey of more than 82 SMEs companies BIB003 . In comparison to larger companies, SMEs lack the competency to scale up their IT security level  . The use of obsolete and non-updated database management system raised a critical IT security gap for SMEs. In consequence, making SMEs less resilient against cyber-attacks and intrusions. The processing and analysis of customer's data by SMEs, on the other hand, has to abide by European Union (EU) legality on data protection and privacy. The lengthy EU data protection law 21 , mooted in 2012, creates an added constraint for SMEs. Predominantly, in view of the lack of financial resources, SMEs could not meet the expenses to engage a legal expert in order to fully grasp the EU's data protection legislation requirements.