AI Architecture (Data Hygiene and Its Impact on Generative AI (GenAI)

In this video, AI Architecture (Data Hygiene and Its Impact on Generative AI (GenAI) cloud and generative AI expert David Linthicum joins host Mike Gibbs again, this time to discuss the role of data integration and data hygiene in generative AI architecture and AI architecture. Key points of the discussion include the importance of data hygiene and generative AI optimization driven by near-real-time data updates. As AI Architects of Cloud AI Architects, you must understand the importance of clean and accurate data for effective AI training and decision-making as part of your GEN AI Architecture.
So if you’re interested in learning more about data hygiene and data integration as part of generative AI architecture and generative AI optimization then this video is for you.
Our guest David has an extensive background (over 30 years of experience) in enterprise technology; and is a globally recognized thought leader, innovator, and influencer in cloud computing, AI, and cybersecurity.
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[@surenlaad]

Absolutely. It is really essential to implement robust data govenrnace practices.Thank you, David and Mike.

[@GoCloudArchitects]

Definitely! Having strong data governance practices in place is important for maintaining data integrity and ensuring its usefulness.

[@markyoshikawa4278]

Hello Mike and David, this is such an important topic to cover! Experiences in everyday life bears that out for instance I've work in places where the customer moved and their product was delivered to the wrong location (in this case data is dynamic). I was in Mexico and the Uber driver took us to the restaurant but the Uber database did not have the new address where the restaurant moved two weeks ago. So I believe data hygiene has to be an on going thing in the case where data changes. Putting on the architecture hat sees this as a fun and rewarding challenge. Don't have a solution yet 🙂. Thank you for bringing this to the fore Mike and David.

[@GoCloudArchitects]

You're totally right! Your experiences show how important it is to keep data accurate, especially when things change. Like with the Uber situation, if the database doesn't have the new address, it causes problems. Making sure data stays clean and up-to-date is a constant job, but it is also a great challenge to tackle, especially from a design point of view.