Matthias Volk studied Business Informatics at the Faculty of Computer Science at the Otto-von-Guericke-University Magdeburg (OVGU) and earned his Master’s degree at the beginning of 2016. Since then, he has been employed as a scientific researcher concurrently pursuing the doctoral degree. During his studies, Mr. Volk gained lots of practical experience as a software developer in different companies, such as Volkswagen. During his scientific career, he participated in many international scientific congresses and projects, not only as a speaker but also as reviewer or session chair. His main research interest lies in the domain of data-intensive systems, related projects, technologies and the management of them.
>
Comparative Study of e-Commerce Ventures: Copycat Enablers in Business Models
In:
Proceedings of the 2nd International Conference on Finance, Economics, Management and IT Business - Volume 1: FEMIB,;
80-90;
2020;
|
Generating Content-Compliant Training Data in Big Data Education
In:
Proceedings of the 12th International Conference on Computer Supported Education;
104-110;
2020;
|
Towards Smart Service Level Agreement (SSLA) Using Blockchain
In:
PACIS 2020 Proceedings;
2020;
|
Determining Potential Failures and Challenges in Data Driven Endeavors: A Real World Case Study Analysis
In:
Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS;
453-460;
2020;
|
Classifying Big Data Taxonomies: A Systematic Literature Review
In:
Proceedings of the 5th International Conference on Internet of Things, Big Data and Security;
267-278;
2020;
|
Improving the Quality Validation of the ETL Process using Test Automation
AMCIS;
2020;
|
In:
Springer Gabler, Wiesbaden (Hrsg.):
Handbuch Digitale Wirtschaft;
1-18;
Springer Gabler, Wiesbaden;
2020;
|
Approaching the (Big) Data Science Engineering Process
In:
Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,;
428-435;
2020;
|
Providing Clarity on Big Data Technologies - The BDTOnto Ontology
In:
International Journal of Intelligent Information Technologies;
49-73;
2020;
|
Towards a Decision Support System for Big Data Projects
In:
WI2020;
2020;
|
Identifying Similarities of Big Data Projects–A Use Case Driven Approach
In:
IEEE (Hrsg.):
IEEE Access ( Volume: 8);
186599 - 186619;
IEEE;
2020;
|
A holistic view of the server consolidation and virtual machines placement problems
In:
15th International Conference on Signal Image Technology & Internet based Systems, SITIS 2019;
Sorrento, Italy;
2019;
|
Machine Learning Techniques for Annotations of Large Financial Text Datasets.
In:
25th Americas Conference on Information Systems, AMCIS 2019, Cancun, Mexico, August 15-17, 201;
2019;
|
In:
Handbuch Digitale Wirtschaft;
1-15;
Springer;
2019;
|
Understanding Issues in Big Data Applications - A Multidimensional Endeavor.
In:
25th Americas Conference on Information Systems, AMCIS 2019, Cancun, Mexico, August 15-17, 2019;
2019;
|
Exploring the Specificities and Challenges of Testing Big Data Systems
In:
15th International Conference on Signal Image Technology & Internet based Systems;
2019;
|
Challenging Big Data Engineering: Positioning of Current and Future Development
In:
Proceedings of the 4th International Conference on Internet of Things, Big Data and Security;
257-268;
2019;
|
Decision-Support for Selecting Big Data Reference Architectures
In:
Proceedings of the 22nd International Conference on Business Information Systems; 2019;
3-17;
2019;
|
An Inventory-Based Mobile Application for Warehouse Management to Digitize Very Small Enterprises
In:
Proceedings of the 22nd International Conference on Business Information Systems;
2019;
|
IT Operation Management A possibility in the flux of digitization Completed Research
In:
Proceedings of the 24th Americas Conference on Information Systems (AMCIS);
1-10;
AIS Electronic Library (AISeL);
2018;
|
IT-Landscape Management in the Higher Educational Institutions
In:
Proceedings of Sixth International Conference on Enterprise Systems;
211-216;
IEEE;
2018;
|
Classifying Big Data Technologies – An Ontology-based Approach
1-10;
AIS Electronic Library (AISeL);
2018;
|
Ask the Right Questions: Requirements Engineering for the Execution of Big Data Projects
In:
Association for Information Systems (Hrsg.):
23rd Americas Conference on Information Systems, {AMCIS} 2017, Boston, MA, USA, August 10-12, 2017;
2017;
|
New E-Commerce User Interest Patterns
In:
IEEE (Hrsg.):
Proceedings 2017 IEEE International Congress on Big Data -BigData Congress-;
2017;
|
Providing Clarity on Big Data Technologies: A Structured Literature Review
In:
David Diaz, Yannis Manolopoulos, Babis Theodoulidis, Mohamed Zaki (Hrsg.):
Proceedings 2017 IEEE 19th Conference on Business Informatics CBI 2017;
IEEE;
2017;
|
How much is Big Data? A Classification Framework for IT Projects and Technologies
In:
Proceedings of the 22nd Americas Conference on Information Systems (AMCIS);
AIS;
2016;
|
The I-ID: an IT Solution to Supplement Conventional Identification Cards - The Air Transportation Systems Use Case
In:
IEEE (Hrsg.):
Proceedings of the 4th International Conference on Enterprise Systems (ES2016;
2016;
|