Data Management: Page

Why enterprise AI depends on the semantic layer

Semantic layers are moving from BI tools into the core analytics stack as AI agents query enterprise data, requiring governed definitions for consistent interpretation.

By Scott Thompson • June 8, 2026

Neo4j’s GraphAware acquisition targets new customer segment

The purchase adds analysis capabilities for government agencies that work on top of the vendor's graph database, expanding its target audience to include analysts.

By Eric Avidon • June 4, 2026

Big data integration techniques and best practices to adopt

Data integration in big data systems is even more complex now because of AI. To succeed, it requires a strategy built on new approaches and strong data management.

By George Lawton • June 4, 2026

Context is the make-or-break layer for AI in production

Your AI model might not be the reason it fails in production. Missing or unclear context throws off the model, leading to untrustworthy outputs that the business can't act on.

By Stephen Catanzano • June 4, 2026

Microsoft boosts Fabric to make it a foundation for AI

New features that feed agents contextually relevant data add breadth to the platform and keep its data and AI capabilities current in a competitive market.

By Eric Avidon • June 2, 2026

Snowflake barrage adds more AI development, analysis tools

A streaming data service and tools that provide agents with contextual awareness highlight the latest from the vendor as it constructs a foundation for agentic enterprises.

By Eric Avidon • June 2, 2026

Fivetran, DBT Labs complete merger to form data layer for AI

The combined capabilities of the newly formed company provide the infrastructure, including data integration and preparation, for agents and other cutting-edge applications.

By Eric Avidon • June 1, 2026

New Starburst platform extends AI to distributed data

The vendor's approach to developing agents and other cutting-edge applications eliminates the time, cost and risks of moving data and could be a competitive differentiator.

By Eric Avidon • May 28, 2026

Why AI forces security-first governance

AI systems fail quietly through drift, biased outputs and degraded judgment. A security-first governance approach gives leaders the visibility and continuous control to scale AI safely.

By Liam Cleary • May 27, 2026

Data observability for AI helps curb poor model performance

Data quality issues get amplified in AI applications. Models can produce confident -- but misleading -- forecasts and conclusions without observability safeguards.

By Stephen Catanzano • May 26, 2026

10 big data challenges and how to address them

Big data initiatives pose various challenges for data leaders and teams. Here are 10 common ones and advice on overcoming them to ensure deployments are successful.

By George Lawton • May 23, 2026

Evolving Alteryx focusing on AI-ready data, logic for agents

As the vendor grows to meet changing customer needs, CEO Andy MacMillan says its goals have expanded beyond its data prep roots to include connecting agents with proper context.

By Eric Avidon • May 20, 2026

Informatica update aims to provide trust foundation for AI

Agents that continuously perform master data management tasks and a headless architecture for data management improve access to data that can be trusted to inform outputs.

By Eric Avidon • May 20, 2026

Latest Alteryx features aim to boost AI-powered automation

Capabilities include an MCP server and a tool that helps transform trusted data and logic into agents, with potential differentiation lying in the empowerment of business users.

By Eric Avidon • May 20, 2026

Latest from Confluent streamlines use of streaming for AI

A fully managed MCP server and machine learning-powered data privacy capabilities aid customers attempting to move real-time AI applications into production.

By Eric Avidon • May 19, 2026

Tracing data lineage in AI systems

Data lineage records how data moves through AI pipelines, turning model debugging, impact analysis and audits into queries rather than manual investigations.

By Stephen Catanzano • May 18, 2026

Data sovereignty expands beyond compliance boundaries

Geopolitical conflict and outages can upend assumptions about where data is controlled and accessed, pushing leaders to plan for jurisdictional risk, resilience and recovery.

By John Moore • May 15, 2026

Understanding data contracts for AI projects

AI models fail silently when upstream data shifts. Data contracts prevent this by making schema, semantics and quality a binding agreement between producers and consumers.

By Stephen Catanzano • May 13, 2026

Power-constrained data architecture curbing AI ambitions

Rising power demands and grid interconnection delays are hampering enterprise AI efforts and altering data strategies, workload placement and resilience planning.

By Sean Kerner • May 13, 2026

Top 10 vector database use cases across industries

Vector databases have become the standard infrastructure for enterprise AI work. These 10 use cases for vector databases show where the technology delivers practical value.

By Donald Farmer • May 11, 2026

Alation intros AI governance suite to ensure compliance

As enterprises launch agents and other cutting-edge applications into production, remaining compliant with evolving regulations is challenging.

By Eric Avidon • May 11, 2026

MongoDB adds new vector, performance capabilities to aid AI

With enterprise data workloads feeding AI pipelines, the longtime database vendor is evolving -- along with competitors -- by building capabilities for cutting-edge development.

By Eric Avidon • May 8, 2026

Data governance metrics: Measure success, identify issues

Implementing a data governance program isn't enough. Data leaders also need to track and analyze various metrics to evaluate its effectiveness and address shortcomings.

By Chris Tozzi • May 8, 2026

Govern citizen development to avoid data pipeline downtime

Low-code/no-code and vibe coding require data leaders to shift from gatekeepers to architects of trust to maintain data integrity and keep pipelines running reliably.

By John Moore • May 8, 2026

Teradata’s latest targets putting agentic AI into production

As many enterprises prepare to move past experimenting with agents, the vendor's new platform is purpose-built to help users move pilots into production.

By Eric Avidon • May 7, 2026