Data management/DataOps/Data Fabric in Data Lakes/Data Meshes/Data Lakehouses
Organisatsiooni nimi
Software Engineering and Information Systems
Kokkuvõte
In case you are interested in Data Management (data governance and/or data quality management) in any of current data architectures, it is possible to discuss your own topic or to collaboratively select the topic based on your knowledge, experience and interest. Topics of both conceptual and purely practical (case studies with pre-defined well-grounded methodology) nature can be proposed and will be considered.
Topics covering or related to sensor-generated data are also welcome.
For DataOps - it is considered as an emerging topic for improving quality and efficiency of data analysis thereby allowing to derive greater value from the available data (internal, i.e., of the organization, external or combining both, i.e., combining the data available within the organization with publicly available data or replying purely on the latter). Considering the specifics of the topic and its emerging popularity with a rather limited body of knowledge and lack of standards, the thesis expect, first, to conduct a SLR on the topic, forming a knowledge base, which would then allow the student to choose a topic of interest for the practical part of the study, depending on the interests and prior experience.
This set of topics suggest that the author/student has at least general knowledge and/or experience in the topic and at least general idea for the thesis. I.e., selection of this topic without prior knowledge in the area is discouraged.
Topics covering or related to sensor-generated data are also welcome.
For DataOps - it is considered as an emerging topic for improving quality and efficiency of data analysis thereby allowing to derive greater value from the available data (internal, i.e., of the organization, external or combining both, i.e., combining the data available within the organization with publicly available data or replying purely on the latter). Considering the specifics of the topic and its emerging popularity with a rather limited body of knowledge and lack of standards, the thesis expect, first, to conduct a SLR on the topic, forming a knowledge base, which would then allow the student to choose a topic of interest for the practical part of the study, depending on the interests and prior experience.
This set of topics suggest that the author/student has at least general knowledge and/or experience in the topic and at least general idea for the thesis. I.e., selection of this topic without prior knowledge in the area is discouraged.
Lõputöö kaitsmise aasta
2024-2025
Juhendaja
Anastasija Nikiforova
Suhtlemiskeel(ed)
inglise keel
Nõuded kandideerijale
Tase
Magister
Märksõnad
Kandideerimise kontakt
Nimi
Anastasija Nikiforova
Tel
E-mail