Challenges to use machine learning in agricultural big data: a systematic literature review
Agricultural Big Data is a set of technologies that allows responding to the challenges of the
new data era. In conjunction with machine learning, farmers can use data to address …
new data era. In conjunction with machine learning, farmers can use data to address …
Big data for open innovation in SMEs and large corporations: Trends, opportunities, and challenges
P Del Vecchio, A Di Minin… - Creativity and …, 2018 - Wiley Online Library
The notion of 'Big Data'has recently been attracting an increasing degree of attention from
scholars and practitioners in an attempt to identify how it may be leveraged to create …
scholars and practitioners in an attempt to identify how it may be leveraged to create …
Human-AI collaboration in data science: Exploring data scientists' perceptions of automated AI
The rapid advancement of artificial intelligence (AI) is changing our lives in many ways. One
application domain is data science. New techniques in automating the creation of AI, known …
application domain is data science. New techniques in automating the creation of AI, known …
Unleashing the potential of AI: Investigating cutting-edge technologies that are transforming businesses
The integration of AI has ushered in a new era of enhanced reliability in digital offerings,
optimization of supply chain processes, and real-time access to invaluable data and …
optimization of supply chain processes, and real-time access to invaluable data and …
Human resources for Big Data professions: A systematic classification of job roles and required skill sets
The rapid expansion of Big Data Analytics is forcing companies to rethink their Human
Resource (HR) needs. However, at the same time, it is unclear which types of job roles and …
Resource (HR) needs. However, at the same time, it is unclear which types of job roles and …
Big data technologies and management: What conceptual modeling can do
The era of big data has resulted in the development and applications of technologies and
methods aimed at effectively using massive amounts of data to support decision-making and …
methods aimed at effectively using massive amounts of data to support decision-making and …
Growth hacking: Insights on data-driven decision-making from three firms
Theoretical background The work explores how Big Data analysis can reshape marketing
decision-making in B2B sector. Deriving from Data-Driven Decision-Making (DDDM) …
decision-making in B2B sector. Deriving from Data-Driven Decision-Making (DDDM) …
Data science applications for predictive maintenance and materials science in context to Industry 4.0
With the revolutionising of the industry to the next generations, machines have become more
complicated. If they are not put to regular maintenance then there is more breakdown and …
complicated. If they are not put to regular maintenance then there is more breakdown and …
Use and adaptations of machine learning in big data—Applications in real cases in agriculture
A Cravero, S Sepúlveda - Electronics, 2021 - mdpi.com
The data generated in modern agricultural operations are provided by diverse elements,
which allow a better understanding of the dynamic conditions of the crop, soil and climate …
which allow a better understanding of the dynamic conditions of the crop, soil and climate …
Building a new culture for quality management in the era of the Fourth Industrial Revolution
S Hyun Park, W Seon Shin, Y Hyun Park… - … Quality Management & …, 2017 - Taylor & Francis
The Fourth Industrial Revolution is coming, and it is changing almost all aspects of human
life, including the culture of quality and quality management (QM) in industry. This paper first …
life, including the culture of quality and quality management (QM) in industry. This paper first …