Welcome to the Alation Resource Center
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?
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Whitepaper
5 Steps to Ensure the Success of Your Cloud Data Migration
The cloud is now a strategic asset, but migrating data can be complex. Learn how to make a seamless transition and turn your cloud data warehouse into a valuable business tool.
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Unleash the Power of Trusted Data for Cutting-Edge AI
Using Alation’s Data Quality Processor (DQP) and Snowflake’s Data Metric Functions (DMFs) you can automate data quality checks, centralize intelligence, and provide teams with reliable, AI-ready data. Together, with Anblicks, we’ll showcase proven strategies, grounded in both practical experience and leading research, for implementing these solutions at scale.
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Improving Data Literacy and Compliance for Energy & Utilities
As regulations continue to evolve in the energy and utilities industry, organisations are increasingly turning to data to ensure compliance while driving better business outcomes. Navigating compliance, pricing strategies & data governance has never been more important.
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Webinar On-Demand
From Data to Business Value: Unlocking the Power of Data Products and AI
Unlocking business value from data and AI requires more than dashboards and reports—it demands data products that deliver real impact. In this panel discussion, Alation brings together visionary data leaders, including an Alation customer and experts from CDO Magazine community, to share how organizations can:
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Webinar On-Demand
Building AI You Can Trust: Driving Business Value with Data Quality, Observability, and Governance
In today’s fast-paced business environment, the pressure to adopt AI and generative AI technologies is greater than ever. But here’s the catch: AI can only deliver value if it’s trusted. How do you ensure your AI systems are accurate, secure, and compliant? It starts with a strong foundation built on data quality, observability, and governance—three critical pillars that work together to create trustworthy AI.
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Building a Robust Data Governance Framework for MAS Regulatory Compliance
In the rapidly evolving regulatory landscape, ensuring compliance with data governance standards is crucial for organizations operating in Singapore. The Monetary Authority of Singapore (MAS) has introduced new data governance guidelines to enhance data protection, transparency, and risk management practices.
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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.
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Webinar On-Demand
Cloud Data Migration in Action
Are you maximizing the value of your data in legacy systems, or is it time to modernize with cloud migration and tap into new opportunities?
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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.
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Webinar On-Demand
Building Trust in AI: Best Practices for AI Governance from IDC's Stewart Bond
As AI becomes increasingly integral to business operations, effective governance is essential to ensure innovation remains safe, auditable, and compliant. According to IDC research, the two top concerns for organizations investing in generative AI solutions are: the lack of GenAI skills or expertise within the organization and the accuracy of AI-generated outcomes. Building AI literacy and leveraging accurate, trusted data are crucial for driving successful AI initiatives.
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