TY - GEN
T1 - Simplifying Data Analysis
T2 - 43rd IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2024
AU - Niedermayr, Daniel
AU - Brunner, Manuel
AU - Tripathi, Shailesh
AU - Jodlbauer, Herbert
N1 - Publisher Copyright:
© IFIP International Federation for Information Processing 2024.
PY - 2024
Y1 - 2024
N2 - Effective data visualization for business applications is crucial in extracting meaningful insights from vast amounts of data generated from various sources. However, there is a need for more visualization tools that combine multiple features, such as complexity reduction methods through the principal component analysis with the data analysis method clustering and interactive visualization. The paper discusses the necessity for novel methods to handle complex and high-dimensional data. It proposes an innovative framework for a visualization tool that integrates complexity reduction, analysis methods, figural features, and various output possibilities. The proposed framework is further practically tested with a dataset of battery electric vehicles (BEV) from the German market. Lastly, the implications for research and practice are discussed, and further research avenues are proposed.
AB - Effective data visualization for business applications is crucial in extracting meaningful insights from vast amounts of data generated from various sources. However, there is a need for more visualization tools that combine multiple features, such as complexity reduction methods through the principal component analysis with the data analysis method clustering and interactive visualization. The paper discusses the necessity for novel methods to handle complex and high-dimensional data. It proposes an innovative framework for a visualization tool that integrates complexity reduction, analysis methods, figural features, and various output possibilities. The proposed framework is further practically tested with a dataset of battery electric vehicles (BEV) from the German market. Lastly, the implications for research and practice are discussed, and further research avenues are proposed.
KW - battery electric vehicles
KW - complexity reduction
KW - data clustering
KW - Data visualization
KW - principal component analysis
KW - visualization framework
UR - http://www.scopus.com/inward/record.url?scp=85204600239&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-71633-1_14
DO - 10.1007/978-3-031-71633-1_14
M3 - Conference contribution
AN - SCOPUS:85204600239
SN - 9783031716324
T3 - IFIP Advances in Information and Communication Technology
SP - 192
EP - 205
BT - Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Complex, and Ambiguous Environments - 43rd IFIP WG 5.7 International Conference, APMS 2024, Proceedings
A2 - Thürer, Matthias
A2 - Riedel, Ralph
A2 - von Cieminski, Gregor
A2 - Romero, David
PB - Springer
Y2 - 8 September 2024 through 12 September 2024
ER -