#195 Zhamak's Corner 18 - Fixing Unnecessary Complications in Serving Data to AI/ML

<p><a href="https://www.patreon.com/datameshradio" rel="noopener noreferrer" target="_blank">Data Mesh Radio Patreon</a> - get access to interviews well before they are released</p><p>Episode list and links to all available episode transcripts (most interviews from #32 on) <a href="https://docs.google.com/spreadsheets/d/1ZmCIinVgIm0xjIVFpL9jMtCiOlBQ7LbvLmtmb0FKcQc/edit?usp=sharing" rel="noopener noreferrer" target="_blank">here</a></p><p>Provided as a free resource by DataStax <a href="https://www.datastax.com/products/datastax-astra?utm_source=DataMeshRadio" rel="noopener noreferrer" target="_blank">AstraDB</a>; George Trujillo's contact info: email (<a href="mailto:george.trujillo@datastax.com" rel="noopener noreferrer" target="_blank">george.trujillo@datastax.com</a>) and <a href="https://www.linkedin.com/in/georgetrujillo/" rel="noopener noreferrer" target="_blank">LinkedIn</a></p><p>For more great content from Zhamak, check out her book on <a href="https://www.oreilly.com/library/view/data-mesh/9781492092384/" rel="noopener noreferrer" target="_blank">data mesh</a>, <a href="https://www.oreilly.com/library/view/software-architecture-the/9781492086888/" rel="noopener noreferrer" target="_blank">a book she collaborated on</a>, <a href="https://www.linkedin.com/in/zhamak-dehghani/" rel="noopener noreferrer" target="_blank">her LinkedIn</a>, and <a href="https://twitter.com/zhamakd" rel="noopener noreferrer" target="_blank">her Twitter</a>.</p><p>So, continuing the conversation about AI and ML's place in data mesh, we start the episode with Zhamak discussing an unnecessary complication we've created in data - why do data sets/assets only have to serve one user or even user persona? Yes, product thinking is about creating reuse but are we thinking reuse across regular analytics and ML/AI at the same time? We need to make it easy to give access in the language of, that native mode of access of, the data consumer. We shouldn't have to care what it is used for, regular analytics, ML, or anything in between. </p><p>T