Big Data-Driven Innovation in Industrial Sectors

Zillner, Sonja; Becker, Tilman; Munné, Ricard; Hussain, Kazim; Rusitschka, Sebnem; Lippell, Helen; Curry, Edward; Ojo, Adegboyega

doi:10.1007/978-3-319-21569-3_9

Cited by 23 publications

(14 citation statements)

References 5 publications

(5 reference statements)

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“…While Big Data technologies such as Map Reduce [14] and Hadoop [63] are the result of big Internet companies such as Google and Yahoo!, the need to handle and process large data sets is quickly extending to other sectors. For instance, the amount of various patient data in the health sector offers new opportunities for better treatments [67] and the advent of smart meters, allows utility provider to better cope with the instabilities of the grid caused by renewable energy sources [33]. From a technological perspective Big Data challenges and technologies can best be described along the so-called 3 V's: Volume, Velocity, and Variety [32].…”

Section: The Various Faces Of Big Datamentioning

confidence: 99%

“…Groups relevant for Smart Cities include health, public sector, energy, and the transport working group. The project has released both an initial version of requirements in these and other sectors [67] as well as a set of technical white papers providing an overview of the state of the art in Big Data technologies [31]. In this chapter, we draw from these results of the BIG project and complement it with the findings from a concrete use case in the energy sector as carried out in the PEC project.…”

Section: Introductionmentioning

confidence: 97%

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Towards a Big Data Analytics Framework for IoT and Smart City Applications

Strohbach¹,

Ziekow²,

Gazis³

et al. 2015

Modeling and Processing for Next-Generation Big-Data Technologies

123

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Abstract. An increasing amount of valuable data sources, advances in Internet of Things and Big Data technologies as well as the availability of a wide range of machine learning algorithms offers new potential to deliver analytical services to citizens and urban decision makers. However, there is still a gap in combining the current state of the art in an integrated framework that would help reducing development costs and enable new kind of services. In this chapter, we show how such an integrated Big Data analytical framework for Internet of Things and Smart City application could look like. The contributions of this chapter are threefold: (1) we provide an overview of Big Data and Internet of Things technologies including a summary of their relationships, (2) we present a case study in the smart grid domain that illustrates the high-level requirements towards such an analytical Big Data framework, and (3) we present an initial version of such a framework mainly addressing the volume and velocity challenge. The findings presented in this chapter are extended results from the EU funded project BIG and the German funded project PEC.

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Section: The Various Faces Of Big Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Towards a Big Data Analytics Framework for IoT and Smart City Applications

Strohbach¹,

Ziekow²,

Gazis³

et al. 2015

Modeling and Processing for Next-Generation Big-Data Technologies

123

View full text Add to dashboard Cite

show abstract

“…Then, the survey was carried out from January to March 2017, using multiple channels such as an online questionnaire form (https://www.aegis-bigdata.eu/what-is-the-current-and-expected-use-of-big-data-technologiesa-glimpse-to-our-aegis-questionnaire-results/), face to face, and telephone interviews. In the case of those interviews, the sample was made up of companies from the IT industry (for the big data technological infrastructure [32,33]) and finance (for the degree of information content of their product and information intensity of the value chain [34]), being an example of data-driven industry [35]. Ultimately, we received 77 replies to the questionnaire out of 110 invitations (a response rate of 70%).…”

Section: Surveymentioning

confidence: 99%

Big Data Use and Challenges: Insights from Two Internet-Mediated Surveys

Rossi¹,

Rubattino²,

Viscusi

2019

Computers

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Big data and analytics have received great attention from practitioners and academics, nowadays representing a key resource for the renewed interest in artificial intelligence, especially for machine learning techniques. In this article we explore the use of big data and analytics by different types of organizations, from various countries and industries, including the ones with a limited size and capabilities compared to corporations or new ventures. In particular, we are interested in organizations where the exploitation of big data and analytics may have social value in terms of, e.g., public and personal safety. Hence, this article discusses the results of two multi-industry and multi-country surveys carried out on a sample of public and private organizations. The results show a low rate of utilization of the data collected due to, among other issues, privacy and security, as well as the lack of staff trained in data analysis. Also, the two surveys show a challenge to reach an appropriate level of effectiveness in the use of big data and analytics, due to the shortage of the right tools and, again, capabilities, often related to a low rate of digital transformation.

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“…Four potential applications for the public sector were described and developed in Zillner et al (2013Zillner et al ( , 2014 for demonstrating the use of big data technologies in the public sector (Table 11.1). …”

Section: Potential Big Data Applications For the Public Sectormentioning

confidence: 99%