Evolve25: Fueling the AI Future Data, Deployment and Tangible Outcomes

Discover why "Hybrid-Multi-Cloud" has moved from a theory to a regulatory necessity and how a unified data fabric overcomes the "Data Gravity" challenge. Learn the four success factors for moving beyond "Pilot Purgatory," including the role of acquisitions like Octopai and Taikun in building a frictionless consumption model. Moorhead shares insights from his global meetings with CEOs on closing the AI skills gap and achieving tangible outcomes in 2025.

Now is the Time for Higher Education Institutions to Master Data Lineage

In today's state, local, and education (SLED) environments—especially higher education—budgets are under constant scrutiny, and the demand for data excellence is constant. That means doing more with fewer resources. One high-impact change to your data workflows that can transform the quality of your data and AI while lowering costs is automating and documenting data lineage.

Self-Service Data Replication with K2K - part 1

First in a 3-part series on self-service K2K replication. This post tackles how to give self-service access to deploy K2K without handing over the keys to your Kafka clusters. Lenses developed K2K (Kafka-to-Kafka) to solve two major problems: This includes making it as self-service as possible so developers can deploy without requiring a PhD in MirrorMaker2. One key design requirement: don’t force engineers to manage credentials to authenticate with Kafka.

Evolve25: AI Readiness and the Future of Intelligent Enterprises with AWS and Cloudera

Discover why the transition from Generative AI to Agentic AI is the key to unlocking $40M+ in business value, even for non-technical users via Cloudera Agent Studio. Learn how the AWS and Cloudera partnership solves the "Data Readiness" challenge by bringing AI to the data, whether on-prem or in the cloud. This session covers critical strategies for AI governance, hybrid architecture, and the shift from task-based tools to autonomous digital workforces.

AI won't fix your SaaS company

Right now, many SaaS leaders are wondering how AI will change building and scaling software companies? AI is transforming how we build software, how teams operate, and how quickly companies launch new products. According to Adam Robinson, founder and CEO of Retention.com, there’s something that most leaders overlook. Your problems won’t get solved by AI but by product-market fit.

The Future of Data & AI is Anywhere Cloud! #Cloudera #AI #Tech #Shorts

Experience a true anywhere cloud with the only data and AI platform that delivers a complete cloud experience regardless of your location. By providing unified security and governance, you can securely access 100% of your data across both on-premises and cloud environments.

Talk to Your Data: How Verisk Finds Risk in Real Time with ThoughtSpot | The Data Chief

Stop searching. Start talking. On podcast, @Verisk_Analytics CDO Louis DiModugno explains how ThoughtSpot lets you “talk with your data” to find hidden risks in real time. No data scientist required. Music: “The Clermont” by Flash Fluharty Licensed via PremiumBeat, ID: P9IHFMDYNZCKLEFZ.

What Is an Agentic Semantic Layer, and Why Does It Matter?

AI can now generate SQL, build dashboards, and answer questions in plain language. But generating queries isn’t the same as understanding a business. The model might not know which revenue definition finance approves, how your fiscal calendar works, or which fields require restricted access. As AI agents become the front door to analytics, the real challenge isn’t query generation; it’s semantic grounding. That’s where the Agentic Semantic Layer becomes essential.