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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.
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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.
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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.
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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.
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Data science and analytics News
New Tableau leader talks vendor's evolution in era of AI
With longtime data and analytics providers pivoting to find their role within AI workflows, Mark Recher takes over during a time of transition for the vendor.
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Database Management News
Actian targets secure, compliant AI with new vector database
The vendor's portable database enables organizations in heavily regulated industries to build AI tools without risking accidental data exposure or regulatory violations.
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Data Warehousing News
Latest AWS data management features target cost control
As the volume and complexity of enterprise data estates increase, and the size of data workloads grows due to AI development, the tech giant aims to help users reduce spending.
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Data Management Strategies Get Started
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.
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Data Integration News
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.
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Data Governance News
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.
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Storage Buying Considerations 2026
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Data Management
Intel and Microsoft: Intelligent Edge to Cloud Solutions
Microsoft and Intel build on long-standing co-engineering efforts to enable differentiated services within Azure. By combining innovative software and services with cutting-edge hardware, the Intel and Microsoft partnership delivers state-of-the-art-edge to cloud solutions for Industrial IoT and computer vision edge AI, SAP on Azure, high-performance computing (HPC), confidential computing, hybrid cloud, Microsoft SQL Server, AI, analytics, and more.
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Increase Productivity with a Scalable Collaboration Solution
Learn how Slack offers significant advantages in scalability, security, platform depth and integrations, engagement, and shared channels are valued by organisations when undertaking digital transformation initiatives.
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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.
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Why AI forces security-first governance
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Tracing data lineage in AI systems
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Understanding data contracts for AI projects
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Problem Solve
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.
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10 big data challenges and how to address them
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Data sovereignty expands beyond compliance boundaries
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Power-constrained data architecture curbing AI ambitions
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How agentic AI governance tackles data, security challenges
AI agents promise real gains -- and pose real risks. Enterprises that move fast without first tightening governance controls might struggle to prevent rogue behavior.
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How to develop a data governance strategy: 7 key steps
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The data ownership blind spots putting organizations at risk
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Controlling data sprawl requires governance discipline
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Data Management/Data Warehousing Basics
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Get Started
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.
-
Get Started
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.
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Get Started
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.
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Vendor Resources
- Software Escrow Solutions to Support Financial Regulations –White Paper
- Data Management for Security Teams –eBook
- From Intent to Intelligence –White Paper
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Data governance
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.
-
Data integration
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.
-
Data management strategies
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.
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