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.
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Methodological Case Study Approach for Detecting Business Model Enablers in Copycat Ventures
In:
International Journal of Organizational and Collective Intelligence 11(4);
35-54;
2021;
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Towards a Systematic Requirements Engineering for IT System-based Business Simulation Games
In:
13th International Conference on Computer Supported Education-Volume 1: CSEDU;
986-391;
2021;
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Hybrid Project Management Methods Efficiency in IT Projects
In:
AMCIS 2021;
2021;
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Towards a Concept for Building a Big Data Architecture with Microservices
In:
6th International Conference on Internet of Things, Big Data and Security-IoTBDS;
2021;
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Examining the Interplay Between Big Data and Microservices-A Bibliometric Review
In:
Complex Systems Informatics and Modeling Quarterly;
2021;
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Applying Test Driven Development in the Big Data Domain-Lessons From the Literature
In:
International Conference on Information Technology (ICIT);
2021;
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A Preliminary Overwiew of the Situation in Big Data Testing
In:
6th International Conference on Internet of Things, Big Data and Security-IoTBDS;
296-302;
2021;
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Challenges in Data Acquisition and Management in Big Data Environments
In:
6th International Conference on Internet of Things, Big Data and Security-IoTBDS;
193-204;
2021;
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A Concept for the Use of Chatbots to Provide the Public with Vital Information in Crisis Situations
In:
ICICT (2) 2021;
281-289;
2021;
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Applying Multi-Criteria Decision-Making for the Selection of Big Data Technologies
In:
AMCIS 2021 Proceedings 10;
2021;
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Automation of Customer Initiated Back Office Processes: A Design Science Research Approach to link Robotic Process Automation and Chatbots
In:
ACIS 2020 Proceedings 15;
2020;
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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;
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Generating Content-Compliant Training Data in Big Data Education
In:
Proceedings of the 12th International Conference on Computer Supported Education;
104-110;
2020;
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Towards Smart Service Level Agreement (SSLA) Using Blockchain
In:
PACIS 2020 Proceedings;
2020;
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Application of NLP to determine the State of Issues in Bug Tracking Systems
In:
2020 International Conference on Data Mining Workshops (ICDMW).IEEE;
53-61;
2020;
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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;
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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;
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Improving the Quality Validation of the ETL Process using Test Automation
AMCIS;
2020;
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Discussing Relations Between Dynamic Business Environments and Big Data Analytics
In:
Complex Systems Informatics and Modeling Quarterly;
58-82;
2020;
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Exploring the Applicability of Test Driven Development in the Big Data Domain
2020;
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In:
Springer Gabler, Wiesbaden (Hrsg.):
Handbuch Digitale Wirtschaft;
1-18;
Springer Gabler, Wiesbaden;
2020;
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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;
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Providing Clarity on Big Data Technologies - The BDTOnto Ontology
In:
International Journal of Intelligent Information Technologies;
49-73;
2020;
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Towards a Decision Support System for Big Data Projects
In:
WI2020;
2020;
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Identifying Similarities of Big Data Projects–A Use Case Driven Approach
In:
IEEE (Hrsg.):
IEEE Access ( Volume: 8);
186599 - 186619;
IEEE;
2020;
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Big Data
Springer Gabler;
Wiesbaden;
2020;
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Towards an Automatized Way for Modeling Big Data System Architectures
In:
23rd International Conference on Business Information Systems;
2020;
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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;
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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;
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In:
Handbuch Digitale Wirtschaft;
1-15;
Springer;
2019;
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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;
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Exploring the Specificities and Challenges of Testing Big Data Systems
In:
15th International Conference on Signal Image Technology & Internet based Systems;
2019;
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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;
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Decision-Support for Selecting Big Data Reference Architectures
In:
Proceedings of the 22nd International Conference on Business Information Systems; 2019;
3-17;
2019;
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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;
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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;
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IT-Landscape Management in the Higher Educational Institutions
In:
Proceedings of Sixth International Conference on Enterprise Systems;
211-216;
IEEE;
2018;
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Classifying Big Data Technologies – An Ontology-based Approach
1-10;
AIS Electronic Library (AISeL);
2018;
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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;
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New E-Commerce User Interest Patterns
In:
IEEE (Hrsg.):
Proceedings 2017 IEEE International Congress on Big Data -BigData Congress-;
2017;
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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;
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