Most AI strategies aren't failing because of models—they’re failing because data is fragmented, siloed, and hard to access. In fact, nearly 8 and 10 organizations say incomplete data access is holding them back. Moving the data drives up cost, introduces latency, and increases compliancy and security risks. Cloudera has introduced the Workflow Data Fabric Zero Copy Connector for ServiceNow to solve this. It allows you to securely leverage nearly 30 exabytes of data under management to power agented workflows without moving the data from wherever it lives.

In this video, we dive into how Click Data Products combine Data Quality, Semantic Types, and business context to create trusted, scalable, and reusable data assets. We explore how semantic types in Qlik help classify and validate data using meaningful business definitions — improving consistency, discoverability, and confidence in analytics and AI-driven insights.

Post-training is rapidly becoming a critical phase of enterprise AI development. To get reliable output from an AI model, organizations must align its terminology (e.g., abbreviation) to fit their specific use cases. But getting started shouldn't require heavy computing resources—you can quickly train an open-source model right on your local device. In this tutorial, we sit down with the ASAP_DPO_Finetuning Cloudera AMP to demonstrate exactly how to align a language model to specific industry standards—in this case, Oil & Gas abbreviations.