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Data governance regulations that executives should know
Growing national and international regulatory compliance demands aim to protect consumer data. Organizations must adhere to regulations or face noncompliance risks.
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Snowflake broadens open-source embrace, ups Iceberg support
To make data more interoperable across systems and usable for AI, the vendor is participating in projects that address data quality, integration, governance and discovery.
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Data governance for AI requires a cross-functional approach
AI systems create risks that span data, security and model integrity. A cross-functional governance model distributes ownership without creating silos.
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AI, analytics push data-in-use protection up priority list
As sensitive data moves into AI pipelines, organizations must evaluate how to protect it during processing and what safeguards IT platforms provide for data in use.
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Snowflake broadens open-source embrace, ups Iceberg support
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Data Governance Get Started
Data governance regulations that executives should know
Growing national and international regulatory compliance demands aim to protect consumer data. Organizations must adhere to regulations or face noncompliance risks.
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Evaluate
Data governance for AI requires a cross-functional approach
AI systems create risks that span data, security and model integrity. A cross-functional governance model distributes ownership without creating silos.
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AI, analytics push data-in-use protection up priority list
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Why enterprise AI initiatives fail without governance
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The database is the new battleground for enterprise AI
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Data domain ownership, data mesh chart path to AI-ready data
That AI initiative won't get off the ground without timely, reliable data. Bringing technology and team practices into sync reduces delays and boosts data readiness.
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SLM vs. LLM: Rightsize data architecture to optimize AI use
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AI data governance guidance that gets you to the finish line
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How to cut data loss risks when employees leave
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Data lineage documentation matters for enterprise reliability
Data lineage is critical to enterprise success. Tracing a data asset's journey through pipelines helps improve data quality, speeds up corrections and builds trust in analytics.
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Build trust on a federated governance model
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Key requirements for data and analytics governance platforms
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Data Management/Data Warehousing Basics
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Data governance regulations that executives should know
Growing national and international regulatory compliance demands aim to protect consumer data. Organizations must adhere to regulations or face noncompliance risks.
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Get Started
How big data collection works: Process, methods, challenges
Before big data can be used in analytics and AI applications, data teams must collect it from various sources. Here's how to create and manage an effective collection process.
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Understanding the layers of the AI‑ready modern data stack
Data infrastructure and practices need an upgrade for the AI era. A modern data stack takes a layered approach that aligns teams and delivers governed, trusted data.
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Data integration
Snowflake broadens open-source embrace, ups Iceberg support
To make data more interoperable across systems and usable for AI, the vendor is participating in projects that address data quality, integration, governance and discovery.
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Data management strategies
Redpanda launches streaming engine optimized for AI
By integrating workload types, the vendor is simplifying data streams for AI while also differentiating itself from its closest competitors.
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Data management strategies
Oracle AI Database update aims to ease developing agents
New vector indexing capabilities and prebuilt agents are designed to simplify building cutting-edge applications and could help differentiate the tech giant from competitors.
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