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dc.contributor.authorIssa, Tomayess
dc.contributor.authorJadeja, B.
dc.date.accessioned2017-12-10T12:39:37Z
dc.date.available2017-12-10T12:39:37Z
dc.date.created2017-12-10T12:20:10Z
dc.date.issued2018
dc.identifier.citationIssa, T. and Jadeja, B. 2018. Big Data—A New Technology Trend and Factors Affecting the Implementation of Big Data in Australian Industries, in Skourletopoulos G., Mastorakis G., Mavromoustakis C., Dobre C., Pallis E. (eds) Mobile Big Data: a roadmap from models to technologies. Lecture Notes on Data Engineering and Communications Technologies, vol 10, pp. 259-287. Cham, Switzerland: Springer.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/59273
dc.description.abstract

Big data is new technology trend and it provides immense advantages. There are too many social networking websites people are using, these websites more than ever before. The data which has been created in the last 5 years is greater than the total size of data accumulated during the preceding. This indicates that people are producing big data knowingly or un-knowingly. In addition to that, every company receives an enormous amount of data in many ways. This data can be transformed into information and information can be converted into knowledge. This knowledge can be very helpful in product marketing. Australian industries can make use of big data. The main objective of this research is to provide more information about big data which is still in its infancy, and find the factors which may affect the Implementation of big data in Australian industries. Big data is still a relatively new field, especially in Australia. It is understandable that big data will become a significant player in Australian industries and that is why it is desirable for these industries to use big data. Big data holds the key to business intelligence and that is why it is important to undertake research on this specific topic. This research study has used a positivist approach and a combination of methodologies. Qualitative and quantitative methodologies have been used and the survey was used as the instrument for gathering data. The survey consists of five sections. The first section is intended to collect the participants’ demographic data. The other four sections are each based on one of the four factors associated with big data: cost, technology, skills and maintenance. The survey has been designed to address these four factors. The Likert scale has been used in this research method. The research design has been explained in detail. The objectives of this research study are: (1) to find factors which determine the Implementation of big data in Australian industries, and (2) to understand the general trend of big data and the technology which can be used to analyze big data. This research provides very important information regarding how big data can be used by different organizations. The participants are employees in the IT department of various industries comprising retail, IT, education, oil-gas and healthcare. These participants’ positions range from entry level to managerial level. The participants’ responses, which constitute the data, were then entered in IBM’s SPSS version 24. The data was entered and analyzed using the factor analysis method. In general, it was found that several factors can affect the Implementation of big data. These factors are: cost, maintenance, skills and technology. The analysis has indicated that statistical skills, IT skills, project management skills and communication skills are important for the people who work with big data. In addition, hardware and software cost, hardware and software maintenance, hardware and software technology also affect the Implementation of big data.

dc.publisherSpringer
dc.relation.uri10.1007/978-3-319-67925-9_11
dc.titleBig Data—A New Technology Trend and Factors Affecting the Implementation of Big Data in Australian Industries
dc.typeBook Chapter
dcterms.source.startPage259
dcterms.source.endPage287
dcterms.source.titleMobile Big Data. Lecture notes on data engineering and communications technologies
dcterms.source.placeGermany
dcterms.source.chapter13
curtin.departmentSchool of Information Systems
curtin.accessStatusFulltext not available


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