Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multi-cloud ecosystem. Analytics Insight brought this interesting topic to our attention in their article, “Data Mesh vs. Data Fabric: What is Making the Best of Metadata?

Both data meshes and data fabrics have a seat at the big data table. Metadata fell out of favor due to its association with static data catalogs. Data mesh is an analytical data architecture and operating model where data is treated as a product and owned by teams that most intimately know and consume the data.

Both data fabrics and data mesh can serve a broad array of business, technical and organizational purposes. Metadata is data about the data or documentation about the information which is required by the users. In data warehousing, metadata is one of the essential aspects.

Metadata makes digital content findable. However, findability works only when a proper taxonomy is in place. Proper indexing against a strong standards-based taxonomy increases the findability of data. Access Innovations is one of a very small number of companies able to help its clients generate ANSI/ISO/W3C-compliant taxonomies.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

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