This comprehensive guide reviews the top AI tools for analytics engineers in 2025, detailing their features and how they empower data teams.
Author
Jenny Salem
Product Marketing at Euno
Head of Product Marketing at Euno. With over 15 years of experience leading marketing teams across startups and enterprises, Jenny brings a rare blend of strategic vision and technical insight. Her roots in cybersecurity and DevOps give her a deep understanding of how data engineering teams work. At Euno, Jenny is focused on transforming the way modern data teams govern and manage data, especially as AI becomes an integral part of the analytics landscape.
Latest blog posts by Jenny Salem
Cut data costs smartly in 2025: avoid waste, fix costly queries, and eliminate zombie data across your stack for competitive advantage.
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Enterprise-grade data lineage is essential for modern data management, powering discovery, governance, optimization, and AI readiness. It transforms static diagrams into a living system.
Discover the top 8 active metadata management tools in 2025 to govern and manage data.
Euno now lets you create active metadata tags based on your own logic.
Explore how Active Metadata Management can help you quickly trace data errors and improve the reliability of your business insights.
You’ve got an AI-driven analytics initiative. Before AI can deliver trusted insights, there’s a fundamental question you need to answer: Are your data assets ready?
Data governance sets the intent and policies for trusted data use, while data management ensures they're followed. AI now bridges the gap by automating compliance.
Tableau vs. dbt: It doesn't have to be a showdown. Learn a framework that helps analysts and engineers work better together.
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