When corporations adopt enterprise AI tools, they often find that their data lake is large but chaotic. Even if you happen to start with fastidiously curated data, poor data change management can have serious consequences further down the road.
Chad Sanderson is the CEO and founding father of Gable.ai, where he helps corporations improve data quality at scale.
I spoke to him concerning the importance of information quality and the way data contracts can make sure that applications built on large amounts of information maintain their integrity.
Q: You have a journalism background. Would you prefer to tell us the way you got into data and your passion for data science and data quality?
Q: You recently spoke at MDS Fest about data contracts and the way these corporations enable federated data management. Would you prefer to briefly explain what it's about?
Q: And it's sort of a garbage-in-the-garbage-out situation. If you alter something very small in your data, it might probably have a profound downward impact.
Q: You are the CEO of an organization called Gable. What do you think that are a number of the biggest challenges for businesses that you would like to solve? How does your platform address a few of these issues?
Q: A giant focus is ensuring data quality to enable AI. But does AI help you do it higher?
Q: If corporations need to use AI, they need data. What do you see as the best opportunities for corporations to administer and develop their data? How can they capitalize on this and prepare for it?
Q: How will things like GDPR and CCPA in California impact how people or corporations approach data quality and security?
Data maintenance, quality management and control have gotten increasingly necessary as corporations develop products based on consistently good data.
If you desire to to learn more about data contracts and how you can get probably the most out of your organization's data, you’ll be able to contact us Chad Sanderson or discover more at Gable.ai.
