Skill Requirements in Big Data: A Content Analysis of Job Advertisements

Gardiner, Adrian; Aasheim, Cheryl L.; Rutner, Paige; Williams, Susan

doi:10.1080/08874417.2017.1289354

Cited by 85 publications

(73 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In order to answer the aforementioned research question, a coding analysis was performed on a dataset composed of job offers, a procedure that is consistent with previous studies (De Mauro et al, 2016;Gardiner et al, 2017). Indeed, job offers have extraordinary information potential.…”

Section: Methodsmentioning

confidence: 99%

“…Given the various needs present in the organisation, the data scientist is only one of the many professional figures required. In this sense, the relevant literature has shown that the presence of data analysts (Davenport et al, 2015), data architects (Gardiner et al, 2017), data engineers (Provost & Fawcett, 2013) and data managers (Miller, 2014) is also usually necessary for organizations that try to use big data to obtain competitive advantages.…”

Section: Professional Figures In the Big Data Eramentioning

confidence: 99%

“…Since there is a link between the analysts and the upper hierarchical levels, the data scientist must also be able to render the data readable and must be equipped with management, marketing and finance skills De Castillo et al, 2015). The data architect, instead, is a figure who is concerned with organizing and maintaining the hardware structures for the collection, storage and analysis of big data (Gardiner et al, 2017). Similarly, the data engineer is a type of electronic-computer engineer who takes care of the software infrastructure (Provost & Fawcett, 2013).…”

Section: Professional Figures In the Big Data Eramentioning

confidence: 99%

See 2 more Smart Citations

Assessing the Impact of Big Data on Large Organizations’ Strategies

Rialti¹,

Faraoni²,

Zollo³

et al. 2019

Symphonya. Emerging Issues in Management

View full text Add to dashboard Cite

Big data and big data analytics' (BDA) importance for business management is growing at an unmatched pace. Such datasets, and the techniques to analyse them, are indeed able to inundate organizations with huge quantities of precious information. Building on this premise, the purpose of this research is to develop a unitary holistic framework on the strategic impact of big data on large organizations. In order to do so, a cognitive map was developed from a coding analysis of 523 job offers on the European labour market coming from 124 large organizations. The results show the effects of big data and BDA on marketing strategies, strategic business intelligence and, finally, operation and supply chain management.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Professional Figures In the Big Data Eramentioning

confidence: 99%

Section: Professional Figures In the Big Data Eramentioning

confidence: 99%

See 1 more Smart Citation

Assessing the Impact of Big Data on Large Organizations’ Strategies

Rialti¹,

Faraoni²,

Zollo³

et al. 2019

Symphonya. Emerging Issues in Management

View full text Add to dashboard Cite

show abstract

“…Lee was able to determine that these positions demanded their candidates to have 'allround' capabilities, beyond just technical skills. More recently, Gardiner et al [17] procured 1,216 job ads with 'Big Data' in the job title from the indeed.com API. The authors then conducted content analyses to investigate how 'Big Data' skills have manifested in labour demand.…”

Section: Related Work and Limitationsmentioning

confidence: 99%

Adaptively selecting occupations to detect skill shortages from online job ads

Dawson

Rizoiu

Johnston

et al. 2019

2019 IEEE International Conference on Big Data (Big Data)

View full text Add to dashboard Cite

Labour demand and skill shortages have historically been difficult to assess given the high costs of conducting representative surveys and the inherent delays of these indicators. This is particularly consequential for fast developing skills and occupations, such as those relating to Data Science and Analytics (DSA). This paper develops a data-driven solution to detecting skill shortages from online job advertisements (ads) data. We first propose a method to generate sets of highly similar skills based on a set of seed skills from job ads. This provides researchers with a novel method to adaptively select occupations based on granular skills data. Next, we apply this adaptive skills similarity technique to a dataset of over 6.7 million Australian job ads in order to identify occupations with the highest proportions of DSA skills. This uncovers 306,577 DSA job ads across 23 occupational classes from 2012-2019. Finally, we propose five variables for detecting skill shortages from online job ads: (1) posting frequency;(2) salary levels; (3) education requirements; (4) experience demands; and (5) job ad posting predictability. This contributes further evidence to the goal of detecting skills shortages in realtime. In conducting this analysis, we also find strong evidence of skills shortages in Australia for highly technical DSA skills and occupations. These results provide insights to Data Science researchers, educators, and policy-makers from other advanced economies about the types of skills that should be cultivated to meet growing DSA labour demands in the future.

show abstract

“…For instance, even the pure testing of a constructed solution can be a sophisticated task (Staegemann et al, 2019). Additionally, this situation is reinforced, by the huge shortage of people that are able to leverage big data (Debortoli et al, 2014;Gardiner et al, 2018;Sivarajah et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Challenging Big Data Engineering: Positioning of Current and Future Development

Volk

Staegemann

Pohl

et al. 2019

Proceedings of the 4th International Conference on Internet of Things, Big Data and Security

View full text Add to dashboard Cite

This contribution examines the terms of big data and big data engineering, considering the specific characteristics and challenges. Deduced by those, it concludes the need for new ways to support the creation of corresponding systems to help big data in reaching its full potential. In the following, the state of the art is analysed and subdomains in the engineering of big data solutions are presented. In the end, a possible concept for filling the identified gap is proposed and future perspectives are highlighted.

show abstract

Skill Requirements in Big Data: A Content Analysis of Job Advertisements

Cited by 85 publications

References 32 publications

Assessing the Impact of Big Data on Large Organizations’ Strategies

Assessing the Impact of Big Data on Large Organizations’ Strategies

Adaptively selecting occupations to detect skill shortages from online job ads

Challenging Big Data Engineering: Positioning of Current and Future Development

Contact Info

Product

Resources

About