Practice Director - Digital & Analytics Practice at HCL Technologies
Real User
2022-10-13T04:26:18Z
Oct 13, 2022
Data mesh is a concept. You need to develop data products and make them discoverable and interoperable to extend the usage of data for business benefits. This happens at its best when it is developed by domain/business units that are experts in the specific areas, due to the simple fact that they know the business and are supporting the data more than anyone else in the organization. This requires many components to come together - domain knowledge, responsible business/data stewards, technology experts, a paradigm shift in ways of working & change management, governance processes & policies, a technology platform, etc. Data fabric is important to make data mesh practical - that is the technology backbone that makes it possible to provide context to data, make data discoverable, enable self-service of data, manage data through stewardship workflows, and more.
Data governance is the set of processes, policies, and technologies that ensure data quality, accuracy, and security throughout its lifecycle. Data governance tools help organizations implement and manage their data governance programs. These tools can automate many tasks involved in data governance, such as data discovery, classification, lineage, and quality assessment.
Data mesh is a concept. You need to develop data products and make them discoverable and interoperable to extend the usage of data for business benefits. This happens at its best when it is developed by domain/business units that are experts in the specific areas, due to the simple fact that they know the business and are supporting the data more than anyone else in the organization. This requires many components to come together - domain knowledge, responsible business/data stewards, technology experts, a paradigm shift in ways of working & change management, governance processes & policies, a technology platform, etc. Data fabric is important to make data mesh practical - that is the technology backbone that makes it possible to provide context to data, make data discoverable, enable self-service of data, manage data through stewardship workflows, and more.