AI starts with trusted data
DataGalaxy gives you a clear framework to manage AI use cases, models, and data with transparency, ownership, and alignment to business and regulatory requirements.
The risk of lack of AI-ready data
Without structure, AI can create more problems than it solves, from model drift to bias, compliance failures, and reputational risk.
- No visibility into how AI decisions are made
- Unclear ownership of models and outcomes
- Poor traceability between training data, models, and results
- Fragmented documentation and versioning
- Gaps in compliance, fairness, and explainability
What you can do with DataGalaxy for AI-ready Data
Establish trust in AI decisions
Align AI initiatives with business strategy
Mitigate risk & ensure compliance
Break silos between data, model, and compliance teams
Start with the “Why” of AI
Good AI starts with a clear business need. Use DataGalaxy to capture ideas, define the problem, align on strategic goals, prioritize, and evaluate value vs. feasibility.
Trusted data for trusted AI
Empower users to trust the datasets fueling your AI by monitoring data quality in real time. Surface quality indicators, flag issues early, and keep your models grounded in reliable, well-governed data.
Track data sources, features, and model lineage
Link models to the datasets, transformations, and outputs they rely on. Understand dependencies and ensure data quality at every step.
Define & share AI policies
Make your AI guidelines accessible and actionable. Document policies around data usage, model validation, fairness, and accountability, then link them to your AI assets and use cases. Keep everyone aligned and reduce risks from the start.
Move from reactive to proactive governance
Talk to an expertEnable compliance collaboration across teams
Use campaigns to run targeted efforts like policy rollouts, ownership validation, or documentation reviews.
Assign tasks, set timelines, and follow up all inside the platform, with no need for external tools or manual follow-up.
Designed for responsible AI practices
DataGalaxy helps you align AI development with frameworks like:
- EU AI Act
- ISO/IEC 42001
- Internal risk and audit controls
- ESG and ethics policies
You can adapt rules, define custom risk scores, and create governance workflows that reflect your own standards.
Give teams access to trusted, compliant data
Empower every user to find and use data that meets your organization’s regulatory standards. With built-in lineage, policies, and access controls, teams can confidently work with data that’s accurate, approved, and always audit-ready.
Integrates with your entire data stack
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Q&A
- Does this help with regulatory frameworks like the EU AI Act?
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Yes. DataGalaxy gives you visibility into data lineage, ownership, and usage policies — key pillars of AI compliance and model transparency.
- How can organizations implement AI governance?
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Organizations implement AI governance by developing comprehensive frameworks that encompass policies, ethical guidelines, and compliance strategies. This includes establishing AI ethics committees, conducting regular audits, ensuring data quality, and aligning AI initiatives with legal and societal standards. Such measures help manage risks and ensure that AI systems operate in a manner consistent with organizational values and public expectations.
- How does a data catalog help with AI risk management?
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A modern data catalog helps identify and track sensitive data, document lineage, and ensure data quality — all of which reduce AI-related risks. It also improves traceability across AI pipelines and enables proactive monitoring.
- How does this integration help scale AI initiatives?
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By aligning Databricks assets with structured governance through DataGalaxy, teams gain clarity on asset ownership, versioning, and business impact. This reduces risks, accelerates model development, and ensures that AI initiatives are scalable, compliant, and aligned with strategic goals.
- How does the portfolio help build a strategic view of Data and AI initiatives?
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It consolidates every use case into a single strategic workspace with dashboards that highlight coverage, progress, alignment with business goals, and areas needing attention. This gives leaders a complete, real-time picture of the organization’s Data and AI efforts.