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Solutions Review Executive Editor Tim King curated this list of notable data management news for the week of March 13, 2026.<\/strong><\/em><\/p>\n Keeping tabs on all the most relevant big data and data management news can be a time-consuming task. As a result, our editorial team aims to provide a summary of the top headlines from the last week in this space. Solutions Review editors will curate vendor product news, mergers and acquisitions, venture capital funding, talent acquisition, and other noteworthy big data and data management news items.<\/p>\n For early access to all the expert insights published on Solutions Review<\/em>, join Insight Jam<\/em><\/a><\/strong><\/span>, a community dedicated to enabling the human conversation on AI.<\/p>\n Actian Launches AI Analyst To Turn Business Glossaries Into A Live Semantic Layer<\/strong><\/p>\n Actian has introduced AI Analyst, a conversational analytics solution that automatically converts existing business glossaries and documentation into a governed Semantic Knowledge Graph. Business users can ask natural-language questions and get explainable answers backed by full traceability of sources, filters, and calculations, reducing hallucinations and metric drift while keeping business logic consistent across teams. The semantic layer updates as definitions change, helping enterprises move from raw data to trusted, query-ready insights in days instead of months.<\/p>\n Read on for more\u2192\u00a0https:\/\/www.prnewswire.com\/news-releases\/actian-unveils-conversational-analytics-solution-with-intelligently-generated-semantic-foundation-for-trusted-insights-302708959.html<\/span><\/a><\/p>\n BigID\u2013Atlan Pair DSPM Signals With Catalog Context For Unified AI Data Governance<\/strong><\/p>\n BigID and Atlan have expanded their integration to deliver what they call the first unified structured and unstructured data catalog for AI governance, combining BigID\u2019s DSPM discovery and classification with Atlan\u2019s active metadata catalog. The joint solution automatically classifies sensitive data across databases, lakes, SaaS apps, and unstructured stores, feeds risk and policy alerts into Atlan, and propagates that context along lineage so security and governance teams share a single view. By embedding security intelligence directly into the catalog experience, CDOs and CISOs can align on guardrails for AI and analytics pipelines instead of managing separate, siloed tools.<\/p>\n Read on for more\u2192\u00a0https:\/\/www.prnewswire.com\/news-releases\/bigid–atlan-introduce-the-first-unified-structured–unstructured-data-catalog-for-ai-governance-302708291.html<\/span><\/a><\/span><\/p>\n Boomi Adds Semantic Context, SAP CDC, And Governance To \u201cActivate\u201d Enterprise Data For AI<\/strong><\/p>\n Boomi is expanding its Enterprise Platform with new data activation capabilities that add a semantic context layer, governed SAP change data capture, and agentic workflow oversight to its integration and data management stack. The platform now maps business concepts across applications so AI agents operate on grounded, consistent meanings, streams SAP data changes into downstream systems under policy controls, and provides transparency into how agents use data in multi-step workflows. Boomi pitches this as shifting from simply moving data to activating it\u2014turning fragmented application data into a living foundation for AI, automation, and analytics.<\/p>\n Read on for more\u2192\u00a0https:\/\/www.businesswire.com\/news\/home\/20260309682526\/en\/Boomi-Activates-Data-for-the-Enterprise<\/span><\/a><\/p>\n CData Connect AI Adds Managed MCP Agent Tools And Zero-Trust Controls For Production AI<\/strong><\/p>\n CData is expanding its Connect AI platform with new agent tooling, an MCP-based gateway, and enterprise-grade governance so AI agents can safely read and write to more than 350 live data sources. The update introduces managed MCP tools, cross-domain identity lifecycle management, and a standardized SQL interface that preserves source-system permissions, letting agents execute multi-step workflows across systems like Salesforce, SAP, and databases without duplicating data. CData positions Connect AI as a production-ready \u201cconnectivity, context, and control\u201d layer that upgrades experimental agents into governed, operational systems.<\/p>\n Read on for more\u2192\u00a0https:\/\/www.prnewswire.com\/news-releases\/cdata-expands-connect-ai-platform-with-new-agent-tooling-and-enterprise-grade-security-to-power-production-ai-deployments-302707005.html<\/span><\/a><\/p>\n Coalesce Buys SYNQ And Launches \u201cCoalesce Quality\u201d To Embed Data Quality In The Operating Layer<\/strong><\/p>\n Coalesce has acquired SYNQ, a modern data observability platform, and is rebranding it as Coalesce Quality to bake lineage-aware data quality checks directly into its data operating layer. Coalesce Quality brings proactive monitoring and impact analysis into the same UI and workflows teams use to design and govern transformations, helping them detect issues early, understand downstream blast radius, and resolve incidents faster. Coalesce pitches the combined platform as a way to move from after-the-fact firefighting to making trusted, high-quality data the default outcome of every pipeline change.<\/p>\n Read on for more\u2192\u00a0https:\/\/coalesce.io\/product-technology\/coalesce-acquires-synq-to-bring-native-data-quality-into-the-data-operating-layer\/<\/span><\/a><\/span><\/p>\n Confluent Cloud For Government Gets FedRAMP Moderate To Become A Streaming Backbone For Public Sector AI<\/strong><\/p>\n Confluent Cloud for Government has achieved FedRAMP Moderate Authorization to Operate on AWS GovCloud (US), making its fully managed data-streaming platform available for federal, state, local, tribal, and supporting commercial organizations. Agencies can now deploy secure, compliant Kafka-based data streaming in days instead of months, offloading operational burden while meeting rigorous federal security controls. Confluent pitches the service as a \u201csecure-by-design data backbone\u201d for mission-critical, real-time applications and AI initiatives in the public sector.<\/p>\n Read on for more\u2192\u00a0https:\/\/www.businesswire.com\/news\/home\/20260310591133\/en\/Confluent-Cloud-for-Government-Achieves-FedRAMP-Moderate-Authorization<\/span><\/a><\/p>\n Cribl Re-architects Search Around \u201cAgentic Telemetry\u201d For AI-Driven Security And IT Ops<\/strong><\/p>\n Cribl has unveiled a new, AI-native Cribl Search experience built on an \u201cagentic telemetry\u201d architecture that structures and enriches data at ingest so AI agents can run orders-of-magnitude more queries without breaking the log budget. Structured data lakes and agent-optimized queries are designed to deliver AI-speed search across Cribl-managed and external data, turning telemetry into continuously queryable fuel for detection, troubleshooting, and observability. By automating normalization and eliminating brittle parsers, Cribl aims to help security and IT teams keep up with the data and query demands of agentic AI while cutting costs and time-to-insight.<\/p>\n Read on for more\u2192\u00a0https:\/\/finance.yahoo.com\/news\/cribl-unveils-agentic-ai-enhancements-130000684.html<\/span><\/a><\/span><\/p>\n Datadog Launches MCP Server So AI Agents Can Safely Tap Live Observability Data<\/strong><\/p>\n Datadog has made its MCP Server generally available, giving AI agents and coding copilots secure, real-time access to unified observability data for debugging and operations. The server exposes Datadog metrics, logs, traces, and incidents via the Model Context Protocol, letting agents analyze issues and take actions inside Datadog while respecting existing security and governance controls. Datadog positions MCP Server as a dynamic protocol layer that simplifies data access for AI workflows and enables more autonomous Dev, Ops, and Sec teams without sacrificing safety.<\/p>\n Read on for more\u2192\u00a0https:\/\/www.datadoghq.com\/about\/latest-news\/press-releases\/datadog-launches-mcp-server\/<\/span><\/a><\/p>\n Denodo 9.4 Adds Conversational AI And A Faster Lakehouse Engine For Agentic Workloads<\/strong><\/p>\n Denodo Platform 9.4 introduces a conversational, agentic AI experience in the Denodo Data Marketplace so business users can explore governed enterprise data through multi-turn natural language queries without knowing schemas or tools. Under the hood, a new Lakehouse Accelerator built on the Velox execution engine delivers up to 4x faster query performance and better resource efficiency for analytics and AI workloads on existing lakehouse architectures, without moving data. Together, the release aims to operationalize agentic AI by pairing a high-performance virtual access layer with explainable, guided data interactions.<\/p>\n Read on for more\u2192\u00a0https:\/\/techafricanews.com\/2026\/03\/11\/denodo-introduces-conversational-ai-access-and-lakehouse-accelerator-in-9-4\/<\/span><\/a><\/span><\/p>\n Grafana Labs Deepens 5-Year AWS Pact To Accelerate Open Observability And AI Insights<\/strong><\/p>\n Grafana Labs has signed a five-year Strategic Collaboration Agreement with AWS to speed adoption of Grafana Cloud on AWS and make open observability easier to deploy at scale. The deal includes co-engineering, AWS credits and marketplace routes for customers, and participation in the AWS ISV Workload Migration Program so organizations can move to fully managed Grafana Cloud while offloading operational overhead. Together the companies aim to deliver AI-powered insights across metrics, logs, and traces on AWS, reducing friction in procurement, migration, and day\u20112 operations.<\/p>\n Read on for more\u2192\u00a0https:\/\/finance.yahoo.com\/news\/grafana-labs-signs-strategic-collaboration-130000489.html<\/span><\/a><\/p>\n Hammerspace\u2013Secuvy Partner To Keep Unstructured Data AI-Ready Across Edge, NAS, And Cloud<\/strong><\/p>\n Hammerspace and Secuvy are partnering to combine Hammerspace\u2019s global data orchestration with Secuvy\u2019s AI-driven discovery and classification, so unstructured data stays continuously governed and AI-ready as it moves across on-premises and cloud. Secuvy\u2019s scanning tags sensitive data and policy context in place, while Hammerspace\u2019s data plane enforces location-aware access, retention, and residency controls from PoC through large-scale AI deployments. The goal is to let enterprises feed AI pipelines from distributed NAS, object stores, and edge locations without losing track of sensitive or regulated information.<\/p>\n Read on for more\u2192\u00a0https:\/\/finance.yahoo.com\/news\/hammerspace-secuvy-partner-scale-data-120000168.html<\/span><\/a><\/span><\/p>\n Liquibase: AI Now Touches Production Databases In 96.5% Of Orgs, But Governance Still Lives In Spreadsheets<\/strong><\/p>\n Liquibase\u2019s 2026 Database DevOps Report finds that 96.5% of organizations have AI interacting with production databases\u2014via analytics, training, internal pilots, or AI-generated SQL\u2014while 68.1% deploy database changes weekly or more often. Yet governance remains largely manual: roughly 90% of database sessions occur outside CI pipelines, and many teams still rely on documentation, ad hoc reviews, and scattered evidence instead of automated controls. Liquibase warns that in the AI era, this governance gap amplifies the blast radius of a single unmanaged change across downstream analytics and AI systems, and urges organizations to shift governance \u201cleft\u201d into developer workflows.\u200b<\/span><\/p>\n Read on for more\u2192\u00a0https:\/\/www.businesswire.com\/news\/home\/20260311497754\/en\/Liquibase-2026-Report-Finds-AI-Now-Interacts-With-Production-Databases-in-96.5-of-Organizations-as-Governance-Automation-Lags<\/span><\/a><\/p>\n Monte Carlo\u2019s New Agent Observability Tracks Context, Performance, Behavior, And Output Quality End-To-End<\/strong><\/p>\n Monte Carlo has expanded its platform with Agent Observability, a set of capabilities that provide unified visibility across four pillars of agent reliability: context, performance, behavior, and outputs. Teams can now evaluate AI-generated fields against warehouse data, use prompt-based checks to catch hallucinations, and monitor latency, token usage, and errors using new Agent Metric Monitors. Agent Trajectory Monitors validate that workflows follow expected tool sequences without loops or skipped steps, while pre-production evaluations and production Agent Evaluation Monitors test agents against golden datasets and continuous quality baselines.<\/p>\n Read on for more\u2192\u00a0https:\/\/www.montecarlodata.com\/blog-agent-observability-announcement-features\/<\/span><\/a><\/span><\/p>\n OneTrust Adds Real-Time, Runtime Controls To Shift AI Governance From Static To Continuous<\/strong><\/p>\n OneTrust is expanding its platform with real-time AI governance and agent oversight capabilities designed to connect policy to operational controls across the AI lifecycle. New features link risk assessments and approved use cases to runtime monitoring and enforcement on key data and AI platforms, helping organizations keep pace as AI becomes embedded in everyday processes. OneTrust says the goal is to move beyond point-in-time compliance toward continuous governance that lets teams innovate quickly while maintaining trust and reducing risk as AI scales.\u200b<\/span><\/p>\n Read on for more\u2192\u00a0https:\/\/www.globenewswire.com\/news-release\/2026\/03\/09\/3251861\/0\/en\/OneTrust-Expands-AI-Governance-to-Meet-the-Demands-of-Scalable-Real-Time-AI.html<\/span><\/a><\/p>\n Precisely\u2013Matillion Partnership Pulls ETL Directly Into The Data Integrity Suite For AI-Ready Pipelines<\/strong><\/p>\n Precisely and Matillion are partnering to embed Matillion\u2019s cloud-native ETL engine inside the Precisely Data Integrity Suite, expanding its Data Integration service with scalable transformation and pipeline automation. The combined offering lets users extract from multiple sources, transform and enrich data, and land it in cloud warehouses and lakes under the same umbrella that already handles data quality, governance, and enrichment. Precisely positions this as a way to reduce pipeline sprawl and accelerate data modernization so organizations can deliver AI-ready, trusted data faster.\u200b<\/span><\/p>\n Read on for more\u2192\u00a0https:\/\/www.precisely.com\/press-release\/precisely-and-matillion-partner-to-accelerate-data-modernization-and-agentic-ai-readiness\/<\/span><\/a><\/span><\/p>\n Snowflake Study: AI Is Creating More Jobs Than It Eliminates\u2014So Far<\/strong><\/p>\n A separate Snowflake report, \u201cThe ROI of Gen AI and Agents,\u201d finds that 77% of organizations report AI-driven job creation versus 46% reporting job loss, and among those seeing both, 69% say AI\u2019s net workforce impact has been positive. Respondents estimate they earn about $1.49 for every dollar spent on AI, but 96% still grapple with data quality, skills, and legacy integration challenges, showing ROI doesn\u2019t mean the hard work is over. Job growth and positive workforce impact are strongest in organizations with multiple AI use cases, suggesting that deeper adoption correlates with better outcomes for both productivity and employment.\u200b<\/span><\/p>\n Read on for more\u2192\u00a0https:\/\/www.snowflake.com\/en\/news\/press-releases\/snowflake-research-reveals-ai-driven-job-creation-outpaces-job-loss-with-77-percent-reporting-workforce-gains\/<\/span><\/a><\/span><\/p>\n Semarchy Survey: Data Management Has Overtaken Cost And Talent As AI\u2019s Biggest Roadblock<\/strong><\/p>\n A new Semarchy survey of 1,000 C\u2011suite leaders finds that 51% now cite data management as their single biggest AI challenge, ahead of both cost and skills, as \u201csignificant\u201d AI investment has tripled year over year and half of organizations now devote more than 20% of tech budgets to AI. Optimism is high\u201492% of leaders are confident they will reach their AI goals, up from 46% in 2025\u2014but 83% say weak data skills and 82% say lack of a clear data strategy are holding them back. About 65% plan to develop \u201cagentic data management\u201d capabilities this year, signaling a shift from one-off dashboards to automated, AI-driven data quality, governance, and integration.<\/p>\n Read on for more\u2192\u00a0https:\/\/www.businesswire.com\/news\/home\/20260309081779\/en\/Data-Management-Overtakes-Cost-and-Talent-as-Top-AI-Challenge-as-65-of-Enterprises-Race-to-Build-Reliable-Agentic-Capabilities<\/span><\/a><\/span><\/p>\n Syndigo Buys Taggstar To Turn Product Content And Social Proof Into A Unified \u201cDigital Shelf\u201d<\/strong><\/p>\n Syndigo has acquired Taggstar, bringing Taggstar\u2019s real-time, AI-contextualized social proof and conversion messaging into Syndigo\u2019s product data cloud and brand\u2013retail network. The combined offering will pair Syndigo\u2019s rich product attributes, images, compliance content, reviews, and ratings with Taggstar\u2019s dynamic messages\u2014like popularity, scarcity, and trending tags\u2014across retailer sites, brand-owned eCommerce, and mobile. Syndigo says the deal lets brands move from static product pages to adaptive, confidence-building experiences that act as virtual sales assistants at the moment of purchase.<\/p>\n Read on for more\u2192\u00a0https:\/\/syndigo.com\/news\/syndigo-acquires-taggstar\/<\/span><\/a><\/p>\n Teradata\u2019s Enterprise Vector Store Adds Multi-Modal, Agentic Capabilities For Autonomous Workflows<\/strong><\/p>\n Teradata is rolling out new agentic and multi-modal features for its Enterprise Vector Store, unifying structured and unstructured data so AI agents can process text, images, and audio at enterprise scale across hybrid environments. The release adds higher-dimensional embeddings (up to 8K), advanced hybrid search, and tight LangChain integration so agents can retrieve context and execute governed actions\u2014not just perform RAG\u2014inside complex workflows. Teradata pitches the platform as a \u201ccontext engine and governance layer\u201d for autonomous AI systems, enabling use cases like claims agents that combine photos, PDFs, and transactional data to make explainable decisions with full audit trails.\u200b<\/span><\/p>\n Read on for more\u2192\u00a0https:\/\/www.teradata.com\/press-releases\/2026\/teradata-enables-ai-agents<\/span><\/a><\/span><\/p>\n Insight Jam<\/em> is Getting Set to Host Donald Farmer for the Expert Briefing: The Last Mile to AI & Why Analytics Leadership Matters on March 31<\/strong><\/p>\n While AI can generate insights at unprecedented speed and scale, it cannot verify those insights against business reality, interpret them within organizational context, or take accountability when decisions go wrong. That responsibility still belongs to people. In this live Insight Jam<\/em> session, Donald Farmer introduces the concept he calls the last mile<\/i>: the critical gap between AI-generated output and trustworthy business action.<\/span><\/p>\n Register free on LinkedIn<\/a><\/p>\n Thought Leaders: Your Executives Need to Hear This Before Your Next AI Project by Nicola Askham<\/strong><\/p>\n AI conversations are happening in most organizations right now, and if you work in data governance, you\u2019re probably right in the middle of it. AI is everywhere. Executives are excited, and rightly so. The possibilities are genuinely exciting: new services, reduced costs, greater efficiencies, things that simply weren\u2019t possible before. It\u2019s shiny, it\u2019s fast-moving, and there\u2019s enormous pressure to get on with it.<\/p>\n Read on Solutions Review<\/em><\/a><\/p>\n The Editors Lens: Why Analytics Leadership Mastermind Groups Solve for the Last Mile of AI<\/strong><\/p>\n As the expectations placed on analytics leaders grow, many are discovering that traditional professional development channels like vendor webinars, industry conferences, and one-off training programs do not\u00a0address the leadership challenges<\/a><\/strong>\u00a0emerging given this AI moment. In response, a growing number of senior analytics professionals are turning to alternative models of leadership development: enter the\u00a0analytics leadership mastermind group<\/a><\/strong>.<\/p>\n Read on Solutions Review<\/em><\/a><\/p>\n Contributor Series: In Search of AI-Ready Data: 6 Steps to Objectively Measuring Data’s AI-Readiness by DataOps.live’s Guy Adams<\/strong><\/p>\n Despite hefty enterprise AI investments, many AI projects are failing to move from pilot to production. There are many reasons for these failures, but one of the biggest is the absence of data that is suitable for AI. That is, companies do not have AI-ready data. But what exactly is AI-ready data, and how do you get there?<\/p>\n Read on Solutions Review<\/em><\/a><\/p>\n –<\/p>\n Insight Jam<\/em> Launches Mesh Lab Episode 2 to Build a Framework for Work & Learning in the Age of AI: The Human Advantage<\/strong><\/p>\n Insight Jam<\/em> Mesh Lab is a year-long, monthly series of expert-led discussions<\/a><\/strong><\/span> dedicated to exploring and shaping the next generation of frameworks for work and learning in the age of AI. Rather than reacting to tools or trends, Mesh Lab is designed to initiate a sustained, cross-sector conversation about how human capability itself must be re-architected as AI becomes embedded across education, enterprise, and leadership.<\/p>\n Watch on Insight Jam<\/em><\/a><\/p>\n Solutions Review <\/i>Surpasses 250K on YouTube to Power Unmatched Media Momentum in Enterprise Tech & the Human Impact of AI<\/b><\/p>\n Solutions Review<\/em>\u00a0has officially surpassed\u00a0250,000 subscribers on YouTube<\/a><\/strong>, a milestone that\u2019s about more than just the number. This moment marks the payoff of a deliberate, two-year strategy\u00a0centered on authoritative video<\/a><\/strong>,\u00a0human-led insight<\/a><\/strong>, and an early recognition of how AI search engines ingest information, assign trust, and surface sources at scale.<\/p>\n Read on Solutions Review<\/em><\/a><\/p>\n Solutions Review<\/em> Editors Launch New ‘Human-AI Ledger’ Newsletter to Chronicle the Human Impact of AI<\/strong><\/p>\n Artificial intelligence is everywhere\u2014but understanding its human impact has never been more urgent. That’s where Solutions Review<\/em>‘s latest newsletter, The Human-AI Ledger<\/i><\/a><\/strong><\/span>, comes in. Designed to chronicle how AI is reshaping the way we learn, work, lead, and live, this newsletter explores the soft side of AI\u2014the non-technical, deeply human dimensions that determine whether this technological revolution helps us thrive or leaves us behind.<\/span><\/p>\nTop Data Management News for the Week Ending March 13,<\/strong> 2026<\/strong><\/h2>\n
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<\/a>Watch this space each week as our editors will share upcoming events, new thought leadership, and the best resources from Insight Jam<\/em>, Solutions Review’s enterprise tech community<\/a><\/strong><\/span> where the human conversation around AI is happening. The goal? To help you gain a forward-thinking analysis and remain on-trend through expert advice, best practices, predictions, and vendor-neutral software evaluation tools.<\/p>\n