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 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.