Data Management: Page

Data domain ownership, data mesh chart path to AI-ready data

That AI initiative won't get off the ground without timely, reliable data. Bringing technology and team practices into sync reduces delays and boosts data readiness.

By John Moore • March 27, 2026

How big data collection works: Process, methods, challenges

Before big data can be used in analytics and AI applications, data teams must collect it from various sources. Here's how to create and manage an effective collection process.

By Mary Pratt • March 26, 2026

The database is the new battleground for enterprise AI

Agentic AI puts new pressure on enterprise databases, exposing gaps in the data access, security enforcement and tooling fragmentation that block production deployment.

By Stephen Catanzano • March 24, 2026

Oracle AI Database update aims to ease developing agents

New vector indexing capabilities and prebuilt agents are designed to simplify building cutting-edge applications and could help differentiate the tech giant from competitors.

By Eric Avidon • March 24, 2026

Q&A: The gap between AI ambitions and data readiness

Ataccama CEO Mike McKee discusses why most organizations aren't ready for AI, why ROI failures are largely a people problem and what the data management industry keeps overlooking.

By Scott Thompson • March 23, 2026

Understanding the layers of the AI‑ready modern data stack

Data infrastructure and practices need an upgrade for the AI era. A modern data stack takes a layered approach that aligns teams and delivers governed, trusted data.

By Tom Walat • March 20, 2026

How to build an effective big data strategy

Big data initiatives won't deliver business benefits without a comprehensive strategy to guide data management and analytics work. Here's how to build one.

By Kathleen Walch • March 19, 2026

Data lineage documentation matters for enterprise reliability

Data lineage is critical to enterprise success. Tracing a data asset's journey through pipelines helps improve data quality, speeds up corrections and builds trust in analytics.

By Chris Tozzi • March 18, 2026

12 top open source databases for enterprise use

Open source databases offer viable alternatives to proprietary systems. This guide offers 12 popular options across relational, NoSQL and source-available technologies.

By Sean Kerner • March 18, 2026

Snowflake intros SnowWork to automate tasks with AI

The platform, which is now in research preview, is designed to provide users with agent-powered collaboration capabilities that can automate actions and workflows.

By Eric Avidon • March 18, 2026

Good governance key to reducing high AI project failure rate

Better governance of cutting-edge applications and the data that feeds them are key to overcoming development obstacles, Databricks exec Craig Wiley said in a recent interview.

By Eric Avidon • March 17, 2026

SLM vs. LLM: Rightsize data architecture to optimize AI use

It doesn't need to be a binary choice. Enterprises are warming up to smaller AI models to meet compliance and cost needs while reserving large models for complex jobs.

By Mary Pratt • March 17, 2026

Qdrant raises $50M in funding to fuel vector database growth

With VCs cautious about investing in data management providers, the financing, which will be used for R&D and go-to-market initiatives, serves as validation of the vendor's vision.

By Eric Avidon • March 12, 2026

Build trust on a federated governance model

Follow this practical blueprint to adopt a modern data governance approach that aligns people, processes and platform to deliver measurable results from AI across the business.

By Andy Hayler, Tom Walat • March 10, 2026

Why agentic AI demands both structured and unstructured data

Agentic AI must access both structured and unstructured data to reason effectively. Converging these data types is the defining operational challenge for enterprise AI in 2026.

By Stephen Catanzano • March 10, 2026

Alation automates governance with latest AI-powered suite

Outcome-based governance, including the newly launched Curation Automation, turns time-consuming data management tasks over to agents and could be a differentiator for the vendor.

By Eric Avidon • March 9, 2026

15 top data catalog software tools to consider using in 2026

Organizations can use numerous tools to build and manage data catalogs. Here are 15 prominent ones that data leaders should consider for their data management needs.

By George Lawton , Craig Stedman • March 9, 2026

Teradata updates vector indexing suite to aid AI development

New capabilities including hybrid search and support for multi-modal embeddings are aimed at helping users access the data needed by agents and other cutting-edge applications.

By Eric Avidon • March 9, 2026

Key requirements for data and analytics governance platforms

Successful governance platforms require business and IT alignment, user-friendly design and scalable architecture to tie governance to measurable outcomes.

By Guido De Simoni • March 9, 2026

CData targets development success with Connect AI update

The vendor's latest launch takes a three-pronged approach toward helping users move pilots into production and could be a competitive differentiator if it delivers on its promise.

By Eric Avidon • March 9, 2026

Data governance responsibilities now belong in the C-suite

To improve business outcomes, leadership must move beyond IT controls and adopt a playbook that treats data as a shared enterprise asset with clear roles and policies.

By Mary Pratt • March 4, 2026

Insightsoftware unifies semantic layer, governance to aid AI

With many enterprises struggling to develop AI tools, the vendor's Simba Intelligence feature set is designed to feed agents and other applications trustworthy, transparent data.

By Eric Avidon • March 4, 2026

AI data governance guidance that gets you to the finish line

As organizations dive into AI adoption, many realize the first real bottleneck is not the model but how to prepare their information so it can be used effectively in AI workflows.

By Ed Scannell • March 3, 2026

How executives can build a responsible AI framework

Building a responsible AI framework requires governance policies, accountability structures, compliant infrastructure and clear metrics to ensure AI systems operate as intended.

By Robert Sheldon • March 2, 2026

Confluent adds A2A support to fuel multi-agent AI networks

Including the open protocol enables users to build an orchestrated network of collaborative agents and could help the vendor distinguish itself from its closest competitors.

By Eric Avidon • Feb. 26, 2026