Data Management: Page

Build a data governance team that delivers results

Regulations, AI and jumbled implementation oversight weaken decision-making. A dedicated team can help bring structure, accountability and consistent outcomes.

By Donald Farmer • May 6, 2026

SAP acquisitions of Dremio, Prior Labs target AI development

The tech giant's latest purchases add a data lakehouse that enables users to access data across systems and tabular foundation models that fuel predictive AI.

By Eric Avidon • May 4, 2026

Qdrant boosts performance, reliability to meet AI needs

As customers look to move past experimentation and put pilots into production, the vendor's new features better prepare its platform for modern enterprise workloads.

By Eric Avidon • April 29, 2026

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.

By Mary Pratt • April 28, 2026

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.

By Eric Avidon • April 28, 2026

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.

By Donald Farmer • April 24, 2026

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.

By Mary Pratt • April 24, 2026

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.

By Stephen Catanzano • April 23, 2026

Controlling data sprawl requires governance discipline

Data sprawl drives higher infrastructure costs, expands security exposure and weakens compliance controls as data proliferates faster than governance can scale.

By Kashyap Kompella • April 22, 2026

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.

By Eric Avidon • April 22, 2026

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.

By Eric Avidon • April 21, 2026

Redis unveils Feature Form to improve AI, ML workloads

Unified batch and streaming pipelines and multi-tenant capabilities that allow teams to isolate work in shared database instances highlight new ML management environment.

By Eric Avidon • April 20, 2026

Reconsider the AI readiness gap in data and analytics

The AI readiness gap is widely framed as temporary, but examining it across three distinct enterprise layers suggests it might be more permanent than the market suggests.

By Scott Thompson • April 20, 2026

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.

By Anne Marie Smith, Ph.D. • April 17, 2026

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.

By Eric Avidon • April 17, 2026

6 key components of a successful data strategy

These six elements are essential parts of an enterprise data strategy that will help meet business needs for information when paired with a solid data architecture.

By Donald Farmer • April 15, 2026

Hybrid search demands reshape retrieval frameworks for AI

As AI workloads mature, enterprises face multiple data platform choices to improve search and retrieval capabilities while meeting governance and operational demands.

By Tom Walat • April 14, 2026

Starburst intros AI assistant to boost analysis, exploration

Built with capabilities that enable it to reason, act and observe, AIDA improves on text-to-SQL translation tools to provide contextually aware query responses.

By Eric Avidon • April 14, 2026

Converged architecture is enterprise AI’s missing foundation

Fragmented AI infrastructure fails in production. Converged data architecture with unified governance offers the path to reliable, scalable enterprise AI.

By Stephen Catanzano • April 13, 2026

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.

By Paul Kirvan • April 8, 2026

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.

By Eric Avidon • April 8, 2026

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.

By Kashyap Kompella • April 8, 2026

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.

By Sean Kerner • April 7, 2026

Why enterprise AI initiatives fail without governance

Enterprise AI pilots succeed in controlled conditions but collapse when scaling exposes the accountability, ownership and explainability gaps that governance was meant to prevent.

By J. Joseph Rusnak • April 1, 2026

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.

By Eric Avidon • March 31, 2026