Data Management

How Cloudera is evolving to stand out in the AI era

By prioritizing on-premises AI deployments, Cloudera is finding a way to evolve that not only keeps it competitive but differentiates it from its peers.

By Eric Avidon • Oct. 29, 2026

Plethora of new Zoho capabilities provide building blocks for AI

New tools, including a semantic layer and a data catalog, turn Zoho's analytics platform into a foundation for AI and keep the vendor competitive with peers.

By Eric Avidon • Oct. 28, 2026

Cloudera launches Blueprints to give building AI a boost

Cloudera aims to simplify AI development with the launch of Blueprints, which are prebuilt accelerators featuring an integration with Nvidia Agent Toolkit.

By Eric Avidon • Oct. 27, 2026

Welcome to TechTarget Data

TechTarget’s relaunch is more than a new look. With expanded reporting, deeper analysis, and clearer coverage across enterprise IT, we’re helping technology leaders understand what matters and what to do next.

By Lisa Schmeiser • Oct. 27, 2026

Meta’s $25B fine underscores risks of data privacy missteps

The fine imposed by a New Mexico judge shows how serious the consequences of misusing customer data can be for companies, as the risks of that grow in the AI era.

By Craig Stedman • Oct. 23, 2026

How CarGurus cleared the roadblocks to its AI initiatives

After the company found that its existing data environment was stalling its AI plans, it launched a multifaceted effort to update its governance, architecture and data practices.

By Mary Pratt • Oct. 23, 2026

Databricks’ latest improves AI memory, infrastructure for agents

The vendor's new additions address some of the real-world problems customers are having as they attempt to deploy agents at scale.

By Eric Avidon • Oct. 22, 2026

Couchbase’s new features target cost, complexity of deploying agents

New capabilities in the vendor's AI Data Plane include native integration with Amazon Bedrock and converting unstructured data to vector embeddings in private networks.

By Eric Avidon • Oct. 20, 2026

Teradata’s new security measures aim to harness AI agents

The vendor's new features, including poly-anonymization to reduce PII exposure address customer needs, bring its privacy and security capabilities in line with its peers.

By Eric Avidon • Oct. 20, 2026

Neo4j joins the context cavalcade with suite for informing AI agents

Context Engine is a set of features that enables the vendor's customers to build knowledge layers for agents to access to inform their actions.

By Eric Avidon • Oct. 20, 2026

5 things to know right now about modern data catalogs

As data catalogs shift from passive registries to platforms that drive AI and analytics, utilizing them to improve data use and governance is a priority for data leaders.

By Craig Stedman • Oct. 19, 2026

How a premortem reveals data modernization project pitfalls

By questioning assumptions early, leaders can spot workflow dependencies, adoption barriers and ownership gaps that a technology-first plan could miss.

By John Moore • Oct. 15, 2026

Bigeye focuses on enforcing AI governance with Policy Engine

AI doesn't work without user confidence in the results; a new feature within Bigeye's Agent Trust Hub aims to reassure users by controlling what data agents can access.

By Eric Avidon • Oct. 14, 2026

How to evaluate the leading data fabric tools and platforms

AI has increased the importance of connecting distributed data. Data leaders should evaluate whether these data fabric vendors offer reliable access while maintaining control.

By George Lawton • Oct. 9, 2026

Security, cost benefits drive the rise of bringing AI to data

Natively integrating models where data lives has proven safer, more cost efficient and effective than porting data into LLMs when building agents and other AI tools.

By Eric Avidon • Oct. 9, 2026

Why data governance struggles to audit shadow AI

Data loss prevention watches known exits, but shadow AI moves data through agents and SaaS integrations. Gateways, local models and sanctioned AI tools close that gap.

By Jelani Harper • Oct. 8, 2026

New Precisely capabilities address common AI development hurdles

The vendor's AI Studio and unified data management suite are designed to simplify development on top of a trusted data foundation

By Eric Avidon • Oct. 6, 2026

Governance teams now emphasize data, AI enablement

In some organizations, data governance programs are now focusing more on enabling employees and AI systems to use data effectively than on controlling its use.

By Craig Stedman • Oct. 6, 2026

The hidden data costs missing from AI budgets

Operational work to shore up a weak data foundation can distort the economics of AI projects. Bringing these costs to light helps clarify ROI and what to prioritize.

By Bill Schmarzo • Oct. 2, 2026

Controlling agents a joint priority for data, AI governance teams

AI agents need context to carry out tasks and guardrails to stop them from going rogue. Data and AI governance teams must work together to ensure both are in place.

By Craig Stedman • Oct. 2, 2026

Evolving MongoDB targets managing agents, performance for AI

A memory and governance layer and an updated database engine further the vendor's progress toward becoming a platform provider for data and AI while helping it remain competitive.

By Eric Avidon • Sept. 29, 2026

Microsoft transforming Fabric into AI’s foundational layer

An integration between Fabric IQ and Copilot helps turn Fabric into a context layer for agents and demonstrates the interconnectedness of Microsoft's many platforms.

By Eric Avidon • Sept. 29, 2026

Databricks buys Row Zero to aid spreadsheet governance for users, AI

The acquisition will enable users to run spreadsheets in the Databricks platform, giving data teams greater governance control over data use by humans and AI agents.

By Craig Stedman • Sept. 25, 2026

Why data governance fails at compliance and how to fix it

Governance policies break down in practice due to unclear ownership, thin resources and weak incentives. Automated controls and monitoring help align them with compliance.

By Chris Tozzi • Sept. 24, 2026

How to prepare enterprise data for advanced AI

AI projects need reliable data, but it's not necessary to prepare all assets at once. Focus the improvements on the structured and unstructured data each use case requires.

By Mary Pratt • Sept. 24, 2026