MLOps approach in the cloud-native data pipeline design
The data modeling process is challenging and involves hypotheses and trials. In the industry, a workflow has been constructed around data modeling. The offered modernized workflow expects to use of the cloud’s full abilities as cloud-native services. For a flourishing big data project, the organizat...
| Main Author: | |
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| Format: | Article |
| Language: | English |
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Széchenyi István University
2021-04-01
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| Series: | Acta Technica Jaurinensis |
| Subjects: | |
| Online Access: | https://acta.sze.hu/index.php/acta/article/view/581 |
| _version_ | 1818238470919815168 |
|---|---|
| author | István Pölöskei |
| author_facet | István Pölöskei |
| author_sort | István Pölöskei |
| collection | DOAJ |
| description | The data modeling process is challenging and involves hypotheses and trials. In the industry, a workflow has been constructed around data modeling. The offered modernized workflow expects to use of the cloud’s full abilities as cloud-native services. For a flourishing big data project, the organization should have analytics and information-technological know-how. MLOps approach concentrates on the modeling, eliminating the personnel and technology gap in the deployment. In this article, the paradigm will be verified with a case-study in the context of composing a data pipeline in the cloud-native ecosystem. Based on the analysis, the considered strategy is the recommended way for data pipeline design. |
| first_indexed | 2024-12-12T12:42:10Z |
| format | Article |
| id | doaj.art-f37691cc557a49dd85d3c62133879135 |
| institution | Directory Open Access Journal |
| issn | 2064-5228 |
| language | English |
| last_indexed | 2024-12-12T12:42:10Z |
| publishDate | 2021-04-01 |
| publisher | Széchenyi István University |
| record_format | Article |
| series | Acta Technica Jaurinensis |
| spelling | doaj.art-f37691cc557a49dd85d3c621338791352022-12-22T00:24:12ZengSzéchenyi István UniversityActa Technica Jaurinensis2064-52282021-04-011511610.14513/actatechjaur.00581477MLOps approach in the cloud-native data pipeline designIstván Pölöskei0Adesso Hungary Kft, Infopark sétány 1, 1117 Budapest, Hungary The data modeling process is challenging and involves hypotheses and trials. In the industry, a workflow has been constructed around data modeling. The offered modernized workflow expects to use of the cloud’s full abilities as cloud-native services. For a flourishing big data project, the organization should have analytics and information-technological know-how. MLOps approach concentrates on the modeling, eliminating the personnel and technology gap in the deployment. In this article, the paradigm will be verified with a case-study in the context of composing a data pipeline in the cloud-native ecosystem. Based on the analysis, the considered strategy is the recommended way for data pipeline design.https://acta.sze.hu/index.php/acta/article/view/581mlopsmachine learningdata pipelinecloud-native |
| spellingShingle | István Pölöskei MLOps approach in the cloud-native data pipeline design Acta Technica Jaurinensis mlops machine learning data pipeline cloud-native |
| title | MLOps approach in the cloud-native data pipeline design |
| title_full | MLOps approach in the cloud-native data pipeline design |
| title_fullStr | MLOps approach in the cloud-native data pipeline design |
| title_full_unstemmed | MLOps approach in the cloud-native data pipeline design |
| title_short | MLOps approach in the cloud-native data pipeline design |
| title_sort | mlops approach in the cloud native data pipeline design |
| topic | mlops machine learning data pipeline cloud-native |
| url | https://acta.sze.hu/index.php/acta/article/view/581 |
| work_keys_str_mv | AT istvanpoloskei mlopsapproachinthecloudnativedatapipelinedesign |