Envisioning Skills for Adopting, Managing, and Implementing Big Data Technology in the 21st Century

Alvarez-Dionisi, Luis Emilio

doi:10.5815/ijitcs.2017.01.03

Cited by 20 publications

(8 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The majority of key contributed variables touch on the core processes of data analytics, such as data modeling, data mining, statistical analysis, data visualization and decision-making. SAS has been recognized as one of the widely adopted statistical tools for Big Data technology (Alvarez-Dionisi, 2017). Risk analytics, one of the various domain-specific analytical tasks (Cao, 2017), appears to draw more attention to AKM job employers.…”

Section: Multiple Correspondence Analysis With Knowledge Skills and Abilities Variables Associated With Hard Skillsmentioning

confidence: 99%

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

Chang

Wang

Hawamdeh

2019

JKM

View full text Add to dashboard Cite

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.

show abstract

Section: Multiple Correspondence Analysis With Knowledge Skills and Abilities Variables Associated With Hard Skillsmentioning

confidence: 99%

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

Chang

Wang

Hawamdeh

2019

JKM

View full text Add to dashboard Cite

show abstract

“…Big data has a strong ability to gain insight into data and the ability to process massive data. In smart tourism, in the face of massive passenger data, big data must be classified and processed to find useful information for passenger tourism in the huge data, and discard useless data [15]. By building a Hadoop platform and implementing data mining technology and artificial neural network algorithms, the complex data problems in the wisdom tourism management model can be well solved.…”

Section: Big Data Technologymentioning

confidence: 99%

Wisdom Tourism Management Mode in the Background of Big Data of the Internet of Things

Huang

Wen

Song

2022

Mobile Information Systems

View full text Add to dashboard Cite

Since the rapid development of the global economy, tourism has become an indispensable entertainment and relaxation item in people’s lives. However, the traditional tourism management mode is slow in conveying tourism information, and there is no reasonable planning of tourism projects for tourists, and it is even more difficult to accurately locate the travel preferences of travelers and make specific travel plans, so that travel resources cannot be fully utilized. Therefore, the Internet of Things big data technology and travel management are combined. For this reason, a wisdom tourism management model based on the big data background of Internet of Things (IoT) is developed. In order to timely arrange and adjust work and travel plans, wisdom tourism makes use of cloud computing, IoT, and other new technologies, with the help of portable mobile terminal devices, so that the tourists can receive timely information about tourism resources, tourism activities, and tourism surroundings to achieve intelligent perception of tourism information, timely arrangement effect. Wisdom tourism can make use of undeveloped tourism resources as much as possible and drive the development of surrounding industries, and promote the economic development of tourist areas. This paper mainly compares the smart tourism management mode with the traditional tourism management mode. The experiment shows that the development degree of the wisdom tourism management mode accounts for 82.8% of the total tourism resources. The traditional tourism management model is only 70.1%, and the GDP of the economy around the tourist area in the wisdom tourism management model in one year is 1.4 times higher than that of the traditional tourism management model. In terms of tourism experience, the wisdom tourism management model is also much better than the traditional tourism management model. And the lower the average age of the experimenter, the higher the favorability of wisdom tourism, up to 98%. It highlights the advantages of the wisdom tourism management model in personalized tourism, tourism development, and surrounding economic growth.

show abstract

“…As depicted in Fig. 14, the suitable technologies available for managing big data environments [23,24] for robotics are Hadoop Ecosystem and NoSQL Databases (Document Stored Database, Key-value Stored Database, Column-oriented Database, Object-oriented Database, and Graph Database).…”

Section: Linking Robotics With Big Datamentioning

confidence: 99%

“…Similarly, db4o (database for objects) is an example of an Object-oriented Database. Finally, Neo4j is an example of a Graph Database [24]. Since this paper is about AI and robotics, it is appropriate to introduce the idea of chatbots.…”

Section: Linking Robotics With Big Datamentioning

confidence: 99%

Teaching Artificial Intelligence and Robotics to Undergraduate Systems Engineering Students

Alvarez-Dionisi¹,

Mittra²,

Balza³

2019

IJMECS

Self Cite

View full text Add to dashboard Cite

The skills of artificial intelligence (AI) and robotics provide a wide window of job opportunities for the following professionals: computer scientists, mechanical engineers, system engineers, computer engineers, biomedical engineers, and electrical engineers. Additionally, other professionals benefiting from AI and robotics' job opportunities are information technologists, informatic engineers, electronic engineers, data scientists, industrial engineers, big data engineers, and related specialists in the dynamic field of engineering robotics. Therefore, the purpose of this research was to study the effort of teaching AI and robotics to undergraduate systems engineering students at the Polytechnic University Institute "Santiago Mariño" in Barinas, Venezuela. Consequently, the methodology used in this academic research was the case study approach, which included three phases, namely Initiation Phase, Fieldwork Phase, and Closing Phase. In that sense, the design of research adopted in this study was based on the development of an exploratory single case study method. As a result, the Theoretical Framework created as a cornerstone of this research highlighted the following three research variables: (1) Robotic Applications, (2) Mechanics of Robotic Manipulation and Computer Vision, and (3) Object-oriented Analysis and Design (OOAD) and Object-oriented (OO) High-level Programming Languages. In conclusion, two nondirectional null hypotheses were tested, leading to the positive answers of the following research questions: (1) "Can undergraduate systems engineering students apply OOAD and OO High-level Programming Languages to analyze, design, and develop Robotic Applications?" and (2) "Can undergraduate systems engineering students use Mechanics of Robotic Manipulation and Computer Vision to analyze, design, and develop Robotic Applications?" as stated in this case study.

show abstract

Envisioning Skills for Adopting, Managing, and Implementing Big Data Technology in the 21st Century

Cited by 20 publications

References 6 publications

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

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

Wisdom Tourism Management Mode in the Background of Big Data of the Internet of Things

Teaching Artificial Intelligence and Robotics to Undergraduate Systems Engineering Students

Contact Info

Product

Resources

About