NIST shifts National Vulnerability Database to risk-based triage as CVE submissions hit record levels

NIST shifts National Vulnerability Database to risk-based triage as CVE submissions hit record levels - SiliconANGLE ...

Zhongqi Zhu Addresses Key Challenges in Vector Database and AI Technology Integration

A study on vector database and AI integration identifies unstable indexing, weak cross-modal fusion, and rigid resource ...

Databricks research shows multi-step agents consistently outperform single-turn RAG when answers span databases and documents

Data teams building AI agents keep running into the same failure mode. Questions that require joining structured data with ...

I asked 5 data leaders about how they use AI to automate - and end integration nightmares

Tech executives explain how they're moving beyond legacy Excel mapping to build AI data pipelines that cut integration ...
VentureBeat

The 'last-mile' data problem is stalling enterprise agentic AI — 'golden pipelines' aim to fix it

Traditional ETL tools like dbt or Fivetran prepare data for reporting: structured analytics and dashboards with stable schemas. AI applications need something different: preparing messy, evolving ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you’ve ever built a predictive model, worked on a ...
Redmond Magazine

Restoring a Database to an Older Version of SQL Server

SQL Server backups cannot be restored to older versions directly. Use Export and Import Data-Tier Application for cross-version database migration. Reconfigure permissions, logins, and connection ...
Forbes

Clean Data: The Cornerstone Of An AI Strategy

AI adoption is accelerating across industries as enterprises move beyond pilot projects to large-scale deployments. Flexera’s 2026 IT Priorities report shows that 94% of IT leaders are actively ...
InfoWorld

AI-augmented data quality engineering

Modern enterprise data platforms operate at a petabyte scale, ingest fully unstructured sources, and evolve constantly. In such environments, rule-based data quality systems fail to keep pace. They ...