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Transform your business with resilient, relevant, and instantly accessible data.
Securing your data while unlocking its full potential is the name of the game. Own guides you through the evolving data landscape with innovative solutions that empower your business.
According to Salesforce, the number one question from customers is, “what should our company be doing today to get ready for Agentforce?”. Our response? Your Agentforce initiatives are only as good as the quality of your data. In this roundtable discussion, we’ll explore key insights, share real-world examples, and provide actionable steps to ensure your organization is truly data-ready for Agentforce.
Learn more about how Own Discover can help you get your data ready for Agentforce and fuel innovations.
Learn how to:
Overcome quality challenges that hinder Agentforce success
Integrate historical data into workflows and Agentforce
Keep your data strategy agile as business needs evolve
Transform your backup data into a powerful asset through Data Cloud to drive smarter Agentforce strategies.
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The buzz at Dreamforce this year was all about CRM + AI + Data + Trust–and we’re here to break down what it means for you. Hear from Product and CRM leaders at Own as they discuss the hottest trends from Dreamforce, strategies for overcoming scaling challenges, and how you can fuel AI and Agentforce strategies with historical Salesforce data.
Ensuring Continuity
Rapidly recover from data breaches, loss, or corruption, while mitigating the chance of them happening at all.
Ensuring Compliance
Improve your security posture while streamlining audits and automating policy-based retention.
Securing Access
Reduce risk by closing security gaps, protecting data in sandboxes, and removing unnecessary data.
Lifecycle Management
Retain data as long as needed without incurring overages or degrading performance.
On-Platform Development
Increase developer velocity by ensuring sandbox data is consistent and accurate.
Off-Platform Analytics
Accelerate insights and AI training by automating the generation of time-series data.
