Data Digest
Blog
Alation Launches Salesforce Connector to Enhance Data Trust
We are excited to announce a new strategic partnership with Salesforce. This partnership will bring data governance and deep insights around data lineage into Salesforce Data Cloud. With this bidirectional integration, Alation joins the Salesforce Data Governance alliance.
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How to Choose the Best Enterprise Data Catalog: Key Criteria Uncovered
It's analyst report season! In the next few months, analyst firms will provide guidance on how to approach the data catalog market and key criteria for choosing a data catalog. These reports can be helpful starting points. But they should be just that: a starting point. With over 12 years of experience and a customer base of nearly 600 enterprises, including 40 of the Fortune 100, we've developed a comprehensive understanding of what truly matters in a data catalog solution to deliver business success. Here are our key criteria uncovered:
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AI for Data Management in 2025: Best Practices, Tools, Use Cases
Key takeaways
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Ethics of AI in Healthcare: Navigating Privacy, Bias, and Trust in 2025
The rapid evolution of artificial intelligence (AI) in healthcare is reshaping how we diagnose, treat, and manage diseases. But with great technological power comes great responsibility. As AI technologies are increasingly integrated into clinical settings, the necessity for ethical frameworks and regulatory guidelines becomes paramount to ensure patient safety, equity, and effective healthcare outcomes. Addressing these concerns is critical to ensuring AI-driven innovations improve patient care while maintaining fairness and safety.
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What is Reinforcement Learning from Human Feedback (RLHF)?
Reinforcement Learning from Human Feedback (RLHF) is a machine learning technique that uses human feedback to optimize AI models to learn more efficiently. Unlike traditional supervised learning, where models are trained on labeled datasets, RLHF allows models to learn through trial-and-error experience and feedback from humans.
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Building AI You Can Trust: Key Takeaways from TDWI Webinar
As organizations increasingly embrace artificial intelligence (AI) to drive innovation and efficiency, the need for trusted data has never been more critical.
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Gartner’s Inaugural Magic Quadrant for Data & Analytics Governance Platforms
Gartner’s introduction of the Magic Quadrant for Data & Analytics Governance Platforms marks the rising importance of data governance for enterprises today. At Alation, we are proud to be recognized in this emerging space for enterprises navigating the complexities of modern data ecosystems.
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The Challenge of Financial Inclusion for the Unbanked: GXS Bank’s Story
Despite progress in expanding access to financial services globally, millions of people remain unbanked. According to the World Bank's Global Findex Database 2021, a lack of money, distance to financial institutions, and documentation requirements are key barriers to financial inclusion. This leads to a vicious cycle where those without credit histories cannot access loans and other banking services to build their financial profiles.
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Unlocking Business Value with Data Governance: Key Trends and Strategies
Establishing a solid data governance program is no longer a luxury—it's a necessity. For organizations striving to harness data's full potential, data governance enables better decision-making, ensures compliance, and delivers operational efficiency. Yet, many businesses still struggle to implement governance initiatives effectively.
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How the NBA Scales Data Best Practices
Despite intense on-court competition between the 30 NBA teams, there is a strong culture of sharing data insights and best practices off the court. Michael James is the SVP of Data and Analytics at the NBA, and he’s run point on nurturing this culture.
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What Is Data Management? Types, Challenges, and Best Practices
Data management encompasses the processes, policies, and technologies that govern the entire lifecycle of data, from its creation and acquisition to its storage, processing, analysis, and eventual archiving or deletion.
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