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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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How to develop a data governance strategy: 7 key steps
A strong data governance strategy enables more effective data use and helps prevent financial, legal and reputational problems. Follow these steps to develop one.
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The data ownership blind spots putting organizations at risk
Organizations can't claim to have good data governance when they still have unowned data. Assigning ownership to siloed and dark data is critical to enterprise success.
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Why enterprise AI stalls between pilot and production
Most enterprise AI programs stall between pilot and production. Closing the operationalization gap requires trusted data, built-in governance and open interoperability.
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Data science and analytics News
Latest SAS capabilities focus on fostering reliable AI
Features including an MCP server and a framework for developing agents aim to enable trustworthy AI-powered analysis while also helping the vendor catch up to its competition.
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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
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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Data Integration News
Data quality, fast failures and quick wins key to AI success
Despite many organizations struggling to realize value from their development initiatives, best practices can help, according to industry experts at Domo's annual user conference.
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Data Governance Get Started
How to develop a data governance strategy: 7 key steps
A strong data governance strategy enables more effective data use and helps prevent financial, legal and reputational problems. Follow these steps to develop one.
Sponsored Sites
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Intelligent Agreement Management
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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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AWS & Red Hat
Simplify App Modernization and Innovation with Red Hat OpenShift Service on AWS
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Evaluate
Why enterprise AI stalls between pilot and production
Most enterprise AI programs stall between pilot and production. Closing the operationalization gap requires trusted data, built-in governance and open interoperability.
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Reconsider the AI readiness gap in data and analytics
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Hybrid search demands reshape retrieval frameworks for AI
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Converged architecture is enterprise AI's missing foundation
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Problem Solve
The data ownership blind spots putting organizations at risk
Organizations can't claim to have good data governance when they still have unowned data. Assigning ownership to siloed and dark data is critical to enterprise success.
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AI, analytics push data-in-use protection up priority list
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Data domain ownership, data mesh chart path to AI-ready data
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SLM vs. LLM: Rightsize data architecture to optimize AI use
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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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Controlling data sprawl requires governance discipline
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6 key components of a successful data strategy
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Data Management/Data Warehousing Basics
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Get Started
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.
-
Get Started
How to develop a data governance strategy: 7 key steps
A strong data governance strategy enables more effective data use and helps prevent financial, legal and reputational problems. Follow these steps to develop one.
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Get Started
How to develop an enterprise data strategy: 12 key steps
Here are 12 to-do items for data leaders developing a data strategy to help their organization use data more effectively for analytics and business decision-making.
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Vendor Resources
- Data Management for Security Teams –eBook
- From Intent to Intelligence –White Paper
- AI Security Starts Here –eBook
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News
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Database management
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.
-
Data management strategies
Google unveils data cloud purpose built for agentic AI
Features including a Knowledge Catalog and cross-cloud lakehouse are aimed at enabling customers to deploy multi-agent systems and could be a competitive edge for the tech giant.
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Data management strategies
Snowflake updates further goal of being control pane for AI
Agentic capabilities that execute workloads based on natural language prompts and access to new data sources facilitate the vendor's ambition to become a hub for agentic systems.
Search Data Management Definitions
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