An investigation of skill requirements for business and data analytics positions: A content analysis of job advertisements

2019 ◽  
Vol 94 (4) ◽  
pp. 243-250 ◽  
Author(s):  
Amit Verma ◽  
Kirill M. Yurov ◽  
Peggy L. Lane ◽  
Yuliya V. Yurova
Keyword(s):  
Content Analysis ◽  
Data Analytics ◽  
Job Advertisements ◽  
Skill Requirements

Skills and Competencies Required for Jobs in Business Analytics

2017 ◽  
Vol 8 (1) ◽  
pp. 1-25 ◽  
Author(s):  
Linda A. Leon ◽  
Kala Chand Seal ◽  
Zbigniew H. Przasnyski ◽  
Ian Wiedenman
Keyword(s):  
Content Analysis ◽  
Human Resources ◽  
Data Analytics ◽  
Career Planning ◽  
Business Analytics ◽  
High Demand ◽  
Data Analyst ◽  
Job Advertisements ◽  
Data Scientist ◽  
Business Analyst

The explosive growth of business analytics has created a high demand for individuals who can help organizations gain competitive advantage by extracting business knowledge from data. What types of jobs satisfy this demand and what types of skills should individuals possess to satisfy this huge and growing demand? The authors perform a content analysis of 958 job advertisements posted during 2014-2015 for four types of positions: business analyst, data analyst, data scientist, and data analytics manager. They use a text mining approach to identify the skills needed for these job types and identify six distinct broad competencies. They also identify the competencies unique to a particular type of job and those common to all job types. Their job type categorization provides a framework that organizations can use to inventory their existing workforce competencies in order to identify critical future human resources. It can also guide individual professionals with their career planning as well as academic institutions in assessing and advancing their business analytics curricula.

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

2017 ◽  
Vol 58 (4) ◽  
pp. 374-384 ◽  
Author(s):  
Adrian Gardiner ◽  
Cheryl Aasheim ◽  
Paige Rutner ◽  
Susan Williams
Keyword(s):  
Big Data ◽  
Content Analysis ◽  
Job Advertisements ◽  
Skill Requirements

scholarly journals EXPRESS: “Get a £10 Free Bet Every Week!” – Gambling Advertising on Twitter: Volume, Content, Followers, Engagement and Regulatory Compliance

2021 ◽  
pp. 074391562199967
Author(s):  
Raffaello Rossi ◽  
Agnes Nairn ◽  
Josh Smith ◽  
Christopher Inskip
Keyword(s):  
Social Media ◽  
Big Data ◽  
Content Analysis ◽  
Volume Content ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Regulatory Compliance ◽  
The Internet ◽  
Policy Recommendations ◽  
Policy Makers

The internet raises substantial challenges for policy makers in regulating gambling harm. The proliferation of gambling advertising on Twitter is one such challenge. However, the sheer scale renders it extremely hard to investigate using conventional techniques. In this paper the authors present three UK Twitter gambling advertising studies using both Big Data analytics and manual content analysis to explore the volume and content of gambling adverts, the age and engagement of followers, and compliance with UK advertising regulations. They analyse 890k organic adverts from 417 accounts along with data on 620k followers and 457k engagements (replies and retweets). They find that around 41,000 UK children follow Twitter gambling accounts, and that two-thirds of gambling advertising Tweets fail to fully comply with regulations. Adverts for eSports gambling are markedly different from those for traditional gambling (e.g. on soccer, casinos and lotteries) and appear to have strong appeal for children, with 28% of engagements with eSports gambling ads from under 16s. The authors make six policy recommendations: spotlight eSports gambling advertising; create new social-media-specific regulations; revise regulation on content appealing to children; use technology to block under-18s from seeing gambling ads; require ad-labelling of organic gambling Tweets; and deploy better enforcement.

Emerging trends in data analytics and knowledge management job market: extending KSA framework

2019 ◽  
Vol 23 (4) ◽  
pp. 664-686 ◽  
Author(s):  
Hsia-Ching Chang ◽  
Chen-Ya Wang ◽  
Suliman Hawamdeh
Keyword(s):  
Content Analysis ◽  
Data Analytics ◽  
Multiple Correspondence Analysis ◽  
Academic Program ◽  
Job Market ◽  
Content Type ◽  
Job Demand ◽  
Experience Levels ◽  
Emerging Trends ◽  
Practical Implications

Purpose This paper aims to investigate emerging trends in data analytics and knowledge management (KM) job market by using the knowledge, skills and abilities (KSA) framework. The findings from the study provide insights into curriculum development and academic program design. Design/methodology/approach This study traced and retrieved job ads on LinkedIn to understand how data analytics and KM interplay in terms of job functions, knowledge, skills and abilities required for jobs, as well as career progression. Conducting content analysis using text analytics and multiple correspondence analysis, this paper extends the framework of KSA proposed by Cegielski and Jones‐Farmer to the field of data analytics and KM. Findings Using content analysis, the study analyzes the requisite KSA that connect analytics to KM from the job demand perspective. While Kruskal–Wallis tests assist in examining the relationships between different types of KSA and company’s characteristics, multiple correspondence analysis (MCA) aids in reducing dimensions and representing the KSA data points in two-dimensional space to identify potential associations between levels of categorical variables. The results from the Kruskal–Wallis tests indicate a significant relationship between job experience levels and KSA. The MCA diagrams illustrate key distinctions between hard and soft skills in data across different experience levels. Practical implications The practical implications of the study are two-fold. First, the extended KSA framework can guide KM professionals with their career planning toward data analytics. Second, the findings can inform academic institutions with regard to broadening and refining their data analytics or KM curricula. Originality/value This paper is one of the first studies to investigate the connection between data analytics and KM from the job demand perspective. It contributes to the ongoing discussion and provides insights into curriculum development and academic program design.

Are Health Sciences Librarians Taking the Evidence-Based Medicine Challenge?

2013 ◽  
Author(s):  
Ping Li ◽  
Lin Wu
Keyword(s):  
Content Analysis ◽  
Literature Review ◽  
Evidence Based Medicine ◽  
Health Sciences ◽  
Evidence Based ◽  
Revue De La Littérature ◽  
Job Advertisements ◽  
Based Medicine

This study sought to find out whether and how health sciences librarians’ roles have been changing to support the evidence-based medicine (EBM) practice. Both content analysis of job advertisements and literature review were employed. Results revealed that there exist some disconnects between what are expected of health sciences librarians in…Cette étude visait à déterminer si le rôle des bibliothécaires du domaine des sciences de la santé a évolué et de quelle manière ce rôle est en mesure de subvenir aux besoins de la médecine fondée sur les preuves (MFP). L’analyse de contenu des offres d’emploi et la revue de la littérature a été employée. Les résultats ont révélé qu’il existe un fossé entre ce que l’on attend des bibliothécaires des sciences de la santé en… 

scholarly journals The Employers’ View of “Work-Ready” Graduates: A Study of Advertisements for Marketing Jobs in Australia

2017 ◽  
Vol 39 (2) ◽  
pp. 82-93 ◽  
Author(s):  
Ellen McArthur ◽  
Krzysztof Kubacki ◽  
Bo Pang ◽  
Celeste Alcaraz
Keyword(s):  
Content Analysis ◽  
Communication Skills ◽  
Time Management ◽  
Digital Marketing ◽  
Business Sector ◽  
Management Communication ◽  
Job Advertisements ◽  
Fit For Purpose ◽  
Job Finding

This study of job advertisements extends our understanding of how employers, rather than researchers, describe the specific skills and attributes sought in candidates for employment in graduate marketing roles in Australia. The article presents the findings of a content analysis of 359 marketing job advertisements downloaded in 2016, in two periods 6 months apart, from the dominant job finding website in Australia, seek.com.au. These data offer detailed primary records authored by employers, and set the research apart from most studies, which rely on generic variables imposed by academics, despite the mooted gap between academia and the business sector. The most demanded attributes included motivation, time management, communication skills, and digital marketing experience. This raises questions about the purpose of a degree, and whether marketing curricula are fit for purpose. The article explores these findings and other preconditions for being “work-ready,” and the study contributes to the underdeveloped employability research from Australia.

scholarly journals The Changing Nature of Work in Academic Libraries

2001 ◽  
Vol 62 (5) ◽  
pp. 407-420 ◽  
Author(s):  
Beverly P. Lynch ◽  
Kimberley Robles Smith
Keyword(s):  
Content Analysis ◽  
Communication Skills ◽  
Academic Libraries ◽  
Academic Library ◽  
Academic Librarians ◽  
Behavioral Skills ◽  
Job Requirements ◽  
Research Libraries ◽  
Job Advertisements ◽  
Professional Degree

A content analysis of 220 job advertisements that appeared in College & Research Libraries between 1973 and 1998 demonstrates that by 1998, all academic library jobs routinely included computer technologies, that instruction had become an integral part of reference work, and that behavioral skills, especially oral and written communication skills, had emerged as new job requirements. The master’s degree from a program accredited by the ALA continues to be widely accepted as the appropriate professional degree for academic librarians.

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