A Technical Perspective of DataCalc : Ad-hoc Analyses on Heterogeneous Data Sources
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
In: 2019 IEEE International Conference on Big Data (Big Data). New York : IEEE, 2019. S. 3864-3873. ISBN: 978-1-7281-0858-2
- Ereignis
-
Veröffentlichung
- (wo)
-
Dresden
- (wer)
-
Technische Universität Dresden
- (wann)
-
2023
- Urheber
-
Luong, Johannes
Habich, Dirk
Lehner, Wolfgang
- URN
-
urn:nbn:de:bsz:14-qucosa2-865020
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:58 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Luong, Johannes
- Habich, Dirk
- Lehner, Wolfgang
- Technische Universität Dresden
Entstanden
- 2023
Ähnliche Objekte (12)
DataCalc : Ad-hoc Analyses on Heterogeneous Data Sources
A Benchmark Framework for Data Compression Techniques
Direct Transformation Techniques for Compressed Data : General Approach and Application Scenarios
Towards Efficient Multi-domain Data Processing
DIPBench: An Independent Benchmark for Data-Intensive Integration Processes
Using Cloud Technologies to Optimize Data-Intensive Service Applications
Model-Driven Development of Complex and Data-Intensive Integration Processes
NeMeSys - A Showcase of Data Oriented Near Memory Graph Processing
Limitations of Intra-operator Parallelism Using Heterogeneous Computing Resources
Teaching In-Memory Database Systems the Detection of Hardware Errors
On-demand re-optimization of integration flows
GignoMDA
DataCalc : Ad-hoc Analyses on Heterogeneous Data Sources
A Benchmark Framework for Data Compression Techniques
Direct Transformation Techniques for Compressed Data : General Approach and Application Scenarios
Towards Efficient Multi-domain Data Processing
DIPBench: An Independent Benchmark for Data-Intensive Integration Processes
Using Cloud Technologies to Optimize Data-Intensive Service Applications
Model-Driven Development of Complex and Data-Intensive Integration Processes
NeMeSys - A Showcase of Data Oriented Near Memory Graph Processing
Limitations of Intra-operator Parallelism Using Heterogeneous Computing Resources
Teaching In-Memory Database Systems the Detection of Hardware Errors
On-demand re-optimization of integration flows
GignoMDA
DataCalc : Ad-hoc Analyses on Heterogeneous Data Sources
A Benchmark Framework for Data Compression Techniques
Direct Transformation Techniques for Compressed Data : General Approach and Application Scenarios
Towards Efficient Multi-domain Data Processing
DIPBench: An Independent Benchmark for Data-Intensive Integration Processes
Using Cloud Technologies to Optimize Data-Intensive Service Applications
Model-Driven Development of Complex and Data-Intensive Integration Processes
NeMeSys - A Showcase of Data Oriented Near Memory Graph Processing
Limitations of Intra-operator Parallelism Using Heterogeneous Computing Resources
Teaching In-Memory Database Systems the Detection of Hardware Errors
On-demand re-optimization of integration flows