Comparing Business Intelligence and Big Data Skills

Debortoli, Stefan; Müller, Oliver; Brocke, Jan vom

doi:10.1007/s12599-014-0344-2

Cited by 167 publications

(105 citation statements)

References 18 publications

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“…Debortoli studied the competencies required for business intelligence and big data professionals by performing an automated content analysis of job ads using a text mining technique called latent semantic analysis (LSA) [14], which is a quantitative method for analyzing qualitative data. Assuming that contexts in which a word appears largely determine the word's meaning, LSA extracts word usage patterns and their meaning through statistical computations [15].…”

Section: Content Analysis Methodology In Current Job Ad Researchmentioning

confidence: 99%

Current Market Demand for Core Competencies of Librarianship—A Text Mining Study of American Library Association’s Advertisements from 2009 through 2014

Yang

Zhang

et al. 2016

Applied Sciences

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As librarianship evolves, it is important to examine the changes that have taken place in professional requirements. To provide an understanding of the current market demand for core competencies of librarianship, this article conducts a semi-automatic methodology to analyze job advertisements (ads) posted on the American Library Association (ALA) Joblist from 2009 through 2014. There is evidence that the ability to solve unexpected complex problems and to provide superior customer service gained increasing importance for librarians during those years. The authors contend that the findings in this report question the status quo of core competencies of librarianship in the US job market.

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Section: Content Analysis Methodology In Current Job Ad Researchmentioning

confidence: 99%

Current Market Demand for Core Competencies of Librarianship—A Text Mining Study of American Library Association’s Advertisements from 2009 through 2014

Yang

Zhang

et al. 2016

Applied Sciences

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“…Descriptive models are sometimes a study's (exploratory studies in particular) main objective (e.g., the competency taxonomy that Debortoli et al (2014) derived from job advertisements). Because topic models represent all associations as probabilities, a researcher can not only present relevant topics along with selected word and document distributions but also group and aggregate topic probabilities by different document meta data (e.g., by author, geography, time), which allows one to rank topics by prevalence, to compare their prevalence for specific subgroups, or to track the evolution of topics over time (for examples, see Grimmer & Stewart, 2013).…”

Section: Challenge #4: Going Beyond Descriptionmentioning

confidence: 99%

Text Mining for Information Systems Researchers: An Annotated Topic Modeling Tutorial

Debortoli¹,

Müller²,

Junglas³

et al. 2016

CAIS

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131

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“…Similar to other studies that aimed for identifying required competences, we used job advertisements as the source of data to gain insights into the competence requirements for financial analysts [5,23]. 50 job advertisements were taken from currently open junior positions in the UK job market in January 2019.…”

Section: Data Collectionmentioning

confidence: 99%

Exploring Digital Competence Requirements for Junior Financial Analysts in the UK Banking Industry

Darvish¹,

Prinz²,

Bick³

2020

Lecture Notes in Computer Science

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Although young adults familiar with digital technology join the workforce and bring in more advanced digital competences, the demand for digital competences in many industries increases even faster. In this study, we place the focus on the banking industry in the United Kingdom and aim for exploring those digital competences that are required for junior financial analysts. For this purpose, we apply a qualitative research approach which consists of two steps. First, we analyze job advertisements and code the identified competences by using the DigComp 2.0 framework. Second, we conduct interviews to validate and discuss our findings from the previous step. Our analysis reveals that the most important required competence categories are information and data literacy, followed by digital content creation. This paper contributes to the research field of digital competences and provides relevant insights for, amongst others, applicants, HR professionals, and training and education providers.

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Comparing Business Intelligence and Big Data Skills

Cited by 167 publications

References 18 publications

Current Market Demand for Core Competencies of Librarianship—A Text Mining Study of American Library Association’s Advertisements from 2009 through 2014

Current Market Demand for Core Competencies of Librarianship—A Text Mining Study of American Library Association’s Advertisements from 2009 through 2014

Text Mining for Information Systems Researchers: An Annotated Topic Modeling Tutorial

Exploring Digital Competence Requirements for Junior Financial Analysts in the UK Banking Industry

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