This thesis aimed to create a data quality and observability framework for the data mesh paradigm. Since the combination of observability and data quality techniques ensures the fundamental concept of trustworthiness. The framework was developed to provide a guide for the entire data intelligence business area of NTT Data and to apply it to a case study using sample clickstream data. The work began with a detailed study of data quality techniques and processes, including the entire data lifecycle from collection to publication. In the context of the work described, libraries such as DataFold, Dbt tests, Great Expectations, and Deequ were evaluated to determine which one(s) could best meet the data quality needs of the case study.