#23 Where and How Can Data Virtualization Work in Data Mesh - Interview w/ Dr. Daniel Abadi

Provided as a free resource by DataStax https://www.datastax.com/products/datastax-astra?utm_source=DataMeshRadio (AstraDB) Don't forget to catch Dr. Abadi at https://starburst.io/info/datanova2022?utm_source=DataMeshRadio (Datanova - the Data Mesh Summit on Feb 9-10th). Thanks to Starburst for sponsoring the transcripts for Data Mesh Radio, check out the transcript https://docs.google.com/document/d/1CkXYjUNMRLl1okJJFmEbzTgTybAAFa-_VC4sOvnFH8s/edit?usp=sharing (here). And check out Starburst's other free data mesh resources https://www.starburst.io/info/data-mesh-resource-center?utm_source=DataMeshRadio (here). In this episode, Scott interviewed Dr. Daniel Abadi, the Darnell-Kanal Computer Science Professor at the University of Maryland with a focus on scalable data management research. Dr. Abadi will be presenting next week at the Data Mesh Summit on Data Fabric and Data Mesh alongside Zhamak and Sanjeev Mohan. This was a pretty wide ranging and free wheeling conversation about data virtualization in general and how it can be used in data mesh. Both agreed that there are many places where data virtualization can play in data mesh, whether in extracting information from operational systems, stitching together a data product once data processing has been done, or at the mesh experience plane re combining data across multiple data products. Dr. Abadi specifically mentions something like a query fabric that makes use of a data virtualization approach, not just tools that only do data virtualization. There is a natural side effect of having multiple different technologies in use - when you give the domains the ability to use what they choose, the difficulty of combining data from multiple sources needs to be solved. There is always a balance between how much you just copy data and how much you can access in the source system and data virtualization can give a few more options rather than all or nothing. As data virtualization has been around as a concept for 30+ years, there is a lot of baggage with the term bu