Whitepaper
Data & AI Readiness Strategy Guide
Leaders are under mounting pressure to implement AI that drives business results. How can they ensure their data is ready to fuel AI models that succeed?
Read this white paper to learn:
Why AI-ready, quality data is critical to AI initiatives
How to create a roadmap for AI strategy (and common pitfalls to avoid)
Best practices for aligning people, process, and technology in support of AI projects
This strategy guide is designed for data management experts who want to learn how a data intelligence platform can help them prepare their data AI, alongside their people and processes, to lead AI initiatives that drive results.
Related resources
Datasheet
Alation Data Governance Datasheet
Alation Data Governance provides the ability to establish and sustain governance programs to centralize data assets’ metadata to remove silos, reduce compliance risk through policies, standards, and controls for those assets, and unlock an organization's data safely for everyone by guiding people to trusted, high-quality, and governed data to make compliant data-driven decisions.
Download
Webinar On-Demand
Navigating AI Governance: How Interac Builds Trust and Innovation
As organizations invest in AI, effective governance is crucial to maintain safety and compliance. But did you know it's also critical for creating a consistent framework for innovation? Interac, a leader in digital payments, has partnered with Alation to build a robust AI governance framework. Hear Mohit Sirpal and Shubneet Bharwani from Interac as they share expert insights on creating a trusted data environment for AI. Learn how Interac leverages data intelligence to enable self-service, transparency, and traceability in their AI processes, ensuring they are prepared for future AI initiatives.
Watch now
Webinar On-Demand
Strategies for AI Governance: Ensuring Trust and Innovation in Advanced Analytics
In today’s rapidly evolving digital landscape, effective data governance is critical for organizations striving to manage diverse and numerous data types. Ensuring the trustworthiness of AI/ML models requires robust governance of both inputs and outputs.
Watch now