#125 Building Trust in Data with Data Governa...

AI agents are moving from demos into production, but many teams run into the same wall: responses that take too long and cost too much. As models grow bigger and reason through more steps before answering, every chained agent adds delay, and that adds up fast at scale. For data a ...  Show more

As agents take over more of the actual coding, the nature of technical work is shifting from producing software to judging it. Engineers increasingly spend their time specifying what should be built and then checking whether an agent's output actually solved the problem, rather t ...  Show more

As organizations implement AI in decision making and how work gets done, trustworthy data is essential to adding value every step of the way. Inadequate data governance or unclear AI ambitions leaves enterprises at risk of falling behind. In this keynote address from Gartner Data ...  Show more

<div class="wp-block-jetpack-markdown"><h2>Summary</h2>

The most important gauge of success for a data platform is the level of trust in the accuracy of the information that it provides. In order to build and maintain that trust it is necessary to invest in defining, monitori ...

<div class="wp-block-jetpack-markdown"><h2>Summary</h2>

Data quality is a concern that has been gaining attention alongside the rising importance of analytics for business success. Many solutions rely on hand-coded rules for catching known bugs, or statistical analysis of rec ...

Data contracts are redefining data quality and governance, and Chad Sanderson, CEO of Gable.ai, joins host Jon Krohn to explain how they can transform your data strategy. He breaks down what data contracts are, how they shift data quality checks closer to production, and why they ...  Show more