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.

Skills and Competencies Required for Jobs in Business Analytics

2018 ◽  
pp. 880-904 ◽  
Author(s):  
Linda A. Leon ◽  
Kala Chand Seal ◽  
Zbigniew H. Przasnyski ◽  
Ian Wiedenman
Keyword(s):  
Content Analysis ◽  
Text Mining ◽  
Human Resources ◽  
Competitive Advantage ◽  
Career Planning ◽  
Business Analytics ◽  
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.

scholarly journals Data Wrangling using Python

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3491-3495
Keyword(s):  
Data Analytics ◽  
Data Science ◽  
Research Work ◽  
Research Area ◽  
Mapping Data ◽  
Data Format ◽  
Data Analyst ◽  
Data Engineering ◽  
Data Scientist ◽  
Term Data

The term Data Engineering did not get much popularity as the terminologies like Data Science or Data Analytics, mainly because the importance of this technique or concept is normally observed or experienced only during working with data or handling data or playing with data as a Data Scientist or Data Analyst. Though neither of these two, but as an academician and the urge to learn, while working with Python, this topic ‘Data engineering’ and one of its major sub topic or concept ‘Data Wrangling’ has drawn attention and this paper is a small step to explain the experience of handling data which uses Wrangling concept, using Python. So Data Wrangling, earlier referred to as Data Munging (when done by hand or manually), is the method of transforming and mapping data from one available data format into another format with the idea of making it more appropriate and important for a variety of relatedm purposes such as analytics. Data wrangling is the modern name used for data pre-processing rather Munging. The Python Library used for the research work shown here is called Pandas. Though the major Research Area is ‘Application of Data Analytics on Academic Data using Python’, this paper focuses on a small preliminary topic of the mentioned research work named Data wrangling using Python (Pandas Library).

MANAJEMEN GURU MODEL GUARDIAN ANGEL MENURUT MUNIF CHATIB

1970 ◽  
Vol 2 (2) ◽  
pp. 85-108
Author(s):  
Ni’matul Khasanah
Keyword(s):  
Content Analysis ◽  
Human Resources ◽  
Lesson Plan ◽  
Qualitative Approach ◽  
Optimal Management ◽  
Guardian Angel ◽  
Humanistic Approach ◽  
Data Content ◽  
Teacher Reports

The background of this research is the fact that the management of improving teacher‟s professionalism is still not effective. The role of teacher as planner, implementer, and developer of curriculum is also not optimal. Management of teachers is needed because teachers have a significant role in the success of learning process. This research was aimed at knowing Guardian Angel‟s concept of teacher management suggested by Munif Chatib and how it develops according to him. The implementation of Guardian Angel model of teacher management was presented through a testimony and direct interviews with Guardian Angel‟s trainees. This research used qualitative approach by studying Munif Chatib‟s books and direct interviews. Data were analyzed with content analysis, which included: (1) literary study of Munif Chatib‟s books, (2) description of Guardian Angel model of teacher management by Munif Chatib. This research found that (1) the concept of Guardian Angel teacher management uses humanistic approach, especially in regard to schedules of consultation, teaching strategies, and assessment through four kinds of teacher reports, including reports of morals, creativity, lesson plan, and student‟s learning results; (2) the basis used is the cornerstone of the scientific human resources and philosophical foundation that teachers carry out the work of teaching, which includes planning, teaching, evaluating, and learning. The first three points are teacher‟s obligations, while the last is their right. Penelitian ini dilatarbelakangi adanya keprihatinan manajemenpeningkatan profesionalitas guru yang belum berjalan efektif. Peranan guru sebagai perencana, pelaksana dan pengembang kurikulum yang belum optimal. Manajemen guru diperlukan mengingat bahwa peran guru amat signifikan bagi setiap keberhasilan proses pembelajaran.Penelitian ini mengungkap tentang manajemen guru Guardian Angel menurut Munif Chatib. Penelitian ini bertujuan untuk mengetahui konsep manajemen guru model Guardian Angel menurut Munif Chatib, dan berkembangannya Guardian Angel dalam pemikiran Munif Chatib. Implementasi manajemen guru model Guardian Angel dihadirkan melalui testimoni dan wawancara langsung dengan peserta pelatihan Guardian Angel. Penelitian ini menggunakan pendekatan kualitatif, dengan melakukan kajian terhadap buku - buku karya Munif Chatib dan wawancara langsung. Teknik anaisis data content analysis. Analisis meliputi: (1) kajian pustaka buku-buku karya Munif Chatib, (2) mendeskripsikan manajemen guru model Guardian Angel dalam pemikiran Munif Chatib.Hasil penelitian menunjukkan bahwa: (1) konsep model manajemen guru Guardian Angel menggunakan pola pendekatan manajemen humanis, terutama dalam jadwal konsultasi, strategi mengajar dan penilaian melalui empat rapor guru, yaitu rapor akhlak, rapor kreativitas, rapor lesson plan dan rapor hasil belajar siswa (2) landasan yang digunakan adalah landasan keilmuan sumber daya manusia dan landasan filosofi bahwa profesi guru mengemban pekerjaan manajemen, yaitu perencanaan , mengajar dan mengevaluasi dan belajar. Tiga hal pertama difahami sebagai kewajiban, sedangkan belajar dimaknai sebagai hak bagi seorang guru (3) Guardian Angel sebagai manajemen quality control yang meliputi: lesson plan, konsultasi, observasi dan umpan balik.

TANTANGAN DAN PENGUATAN IDEOLOGI PANCASILA DALAM MENGHADAPI ERA REVOLUSI INDUSTRI 4.0

2019 ◽  
Vol 2 (02) ◽  
pp. 66-78
Author(s):  
Nurul Fadilah
Keyword(s):  
Content Analysis ◽  
National Identity ◽  
Data Analysis ◽  
Data Collection ◽  
Human Resources ◽  
Research Method ◽  
Industrial Revolution ◽  
Qualitative Approach ◽  
The State ◽  
Way Of Life

The ideology of Pancasila as a way of life, the basis of the state, and national identity has a various challenge from time to time so that the existence of Pancasila as an Ideology must be maintained, especially in industrial revolution 4.0. The research method used is a qualitative approach by doing study of literature. In data collection the writer used documentation while in techniques data analysis used content analysis, inductive and descriptive. Results of the research about challenges and strengthening of the Pancasila Ideology in facing the era of the industrial revolution 4.0 are: (1)  grounding Pancasila, (2) increasing professional human resources based on Pancasila’s values, (3) maintaining the existence of Pancasila as the State Ideology.

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.

scholarly journals BIG DATA BUSINESS ANALYTICS AS A STRATEGIC ASSET FOR HEALTH CARE INDUSTRY

2019 ◽  
Vol 01 (02) ◽  
pp. 12-20 ◽  
Author(s):  
Smys S ◽  
Vijesh joe C
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Health Care Industry ◽  
Customer Relationship ◽  
Business Strategies ◽  
Business Analytics ◽  
Care Industry ◽  
Strategic Assets

The big data includes the enormous flow of data from variety of applications that does not fit into the traditional data base. They deal with the storing, managing and manipulating of the data acquired from various sources at an alarming rate to gather valuable insights from it. The big data analytics is used provide with the new and better ideas that pave way to the improvising of the business strategies with its broader, deeper insights and frictionless actions that leads to an accurate and reliable systems. The paper proposes the big data analytics for the improving the strategic assets in the health care industry by providing with the better services for the patients, gaining the satisfaction of the patients and enhancing the customer relationship.

scholarly journals Career Success According to New Graduates: Implications for Counseling and Management

2019 ◽  
Vol 29 ◽  
Author(s):  
Marina Cardoso de Oliveira ◽  
Lucy Leal Melo-Silva ◽  
Maria do Céu Taveira ◽  
Flávia Leandra Jorge Postigo
Keyword(s):  
Qualitative Research ◽  
Human Resources ◽  
Career Counseling ◽  
Career Success ◽  
Career Planning ◽  
Human Resources Management ◽  
Social Recognition ◽  
New Graduates ◽  
Human Resources Managers ◽  
Subjective Confidence

Resumo Qualitative research on career success has been encouraged across different category of workers. This qualitative research sought to explore how do new graduates define career success and also highlight some implications for career counseling and Human Resources management. Sample included nine new graduates from two different regions of Brazil, divided in two focus groups. Discourse analysis based on interpretative repertoire approach was used for the data analyses. The graduates’ definitions emphasized both subjective (confidence in the future, career planning, professional identity construction, work adjustment, and satisfaction with the career path) and objective (work in the area of graduation with a good salary, financial independence, social recognition) career outcomes. The meanings identified in this study reinforced the multidimensional nature of the construct and also could help career counselors and human resources managers better plan their interventions contributing to new graduates’ career success during university-to-work transition.

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