{"id":20640,"date":"2026-04-28T20:59:12","date_gmt":"2026-04-28T20:59:12","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/20640\/"},"modified":"2026-04-28T20:59:12","modified_gmt":"2026-04-28T20:59:12","slug":"google-reimagines-the-data-as-an-agentic-data-platform","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/20640\/","title":{"rendered":"Google reimagines the data as an agentic data platform"},"content":{"rendered":"

The modern data stack might already be the new legacy. In response, Google Cloud is rebuilding for a world where AI agents \u2014 not humans \u2014 are the primary users of data infrastructure<\/a>, unveiling an agentic data platform called Agentic Data Cloud<\/a> designed for that new era.<\/p>\n

This is a fundamentally different architecture, according to Yasmeen Ahmad<\/a> (pictured), managing director of product management, data and AI cloud at Google Cloud.\u00a0The traditional stack was engineered around SQL engines and optimized for human analysis. Instead, the emergent agentic data platform must support vector search and reasoning, with thousands of tools and multi-step inference instead of a handful of brittle application programming interfaces.<\/p>\n

\u201cWe\u2019re no longer thinking about human personas like data scientists [or] data engineers,\u201d Ahmad said. \u201cWe\u2019re [considering] agents as the persona, because we really believe agents are going to be operating data platforms. There will be humans, but humans are taking a much higher-level orchestration role, not the doer role.\u201d<\/p>\n

Ahmad spoke with theCUBE\u2019s\u00a0Dave Vellante<\/a>\u00a0at\u00a0Google Cloud Next<\/a>, during an exclusive broadcast on theCUBE, SiliconANGLE Media\u2019s livestreaming studio. They discussed how Google Cloud is evolving into an agentic data platform, why context is the missing layer in most enterprise AI architectures and what the cross-cloud lakehouse means for enterprises trying to avoid data lock-in. (* Disclosure below.)<\/p>\n

Agentic data platform architecture centers on context and cross-cloud access<\/p>\n

Google Cloud\u2019s agentic data platform is built on three interlocking layers: the AI Hypercomputer at the base, engineered for the latency and throughput demands of agent swarms; a cross-cloud lakehouse above that, built on Apache Iceberg; and Knowledge Catalog<\/a>, sandwiched between raw data and the AI model. All of this, especially the cross-cloud layer, would have been unthinkable until recently, according to Ahmad.<\/p>\n

\u201cA year ago, if you asked me this, I don\u2019t think it would have been possible,\u201d Ahmad said, referencing cross-cloud capability. \u201cIceberg has become a de facto open standard. That is enabling both Google and our partner ecosystem to share data in ways and with ease that we just couldn\u2019t before.\u201d<\/p>\n

The most critical layer is Knowledge Catalog \u2014 a context and intelligence layer between raw data and the AI model that Google found supplies the missing 50% accuracy that clean, well-structured data alone cannot, according to Ahmad. That context encompasses business meanings, entity relationships, access governance and ranked retrieval logic, which Google is now autogenerating for unstructured data<\/a> using the same hybrid search stack that powers Google Search. Knowledge Catalog also connects to the \u201csystem of action\u201d \u2014 the tools and skills that let agents move beyond data retrieval to execute orders in an ERP or activate campaigns in a CRM. Google launched Data Agent Kit to deliver that capability, packaging agents into modular tools and skills plugging directly into Cloud Code, VS Code and Gemini CLI.<\/p>\n

\u201cThe models have gotten so good that if you give them tools and skills \u2014 data engineering tools, data science tools \u2014 the models can do a lot of hard, heavy-lifting for you,\u201d Ahmad said.<\/p>\n

While agents may have incredible capabilities, the cultural shift may be the hard part. Shopify\u2019s VP of engineering has reframed leadership itself \u2014 asking his team to think of themselves not as owners of workflows but as managers of agents, Ahmad noted. Some human-centric workflows clearly aren\u2019t being redesigned; they\u2019re being deleted entirely.<\/p>\n

\u201cIf you\u2019re not adapting and getting onto that AI curve now, somebody out there is retransforming and redesigning your entire industry,\u201d Ahmad said. \u201cEverybody has in their hands these powerful, capable models to go invent the future.\u201d<\/p>\n

Here\u2019s the complete video interview, part of SiliconANGLE\u2019s and theCUBE\u2019s coverage of\u00a0Google Cloud Next<\/a>:<\/p>\n

(* Disclosure: TheCUBE is a paid media partner for Google Cloud Next. Sponsors of theCUBE\u2019s event coverage do not have editorial control over content on theCUBE or SiliconANGLE.)<\/p>\n

Photo: SiliconANGLE<\/p>\n

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About SiliconANGLE Media<\/p>\n

SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-time audience engagement. As the parent company of SiliconANGLE<\/a>, theCUBE Network<\/a>, theCUBE Research<\/a>, CUBE365<\/a>, theCUBE AI<\/a> and theCUBE SuperStudios \u2014 with flagship locations in Silicon Valley and the New York Stock Exchange \u2014 SiliconANGLE Media operates at the intersection of media, technology and AI.<\/p>\n

Founded by tech visionaries John Furrier and Dave Vellante, SiliconANGLE Media has built a dynamic ecosystem of industry-leading digital media brands that reach 15+ million elite tech professionals. Our new proprietary theCUBE AI Video Cloud is breaking ground in audience interaction, leveraging theCUBEai.com neural network to help technology companies make data-driven decisions and stay at the forefront of industry conversations.<\/p>\n","protected":false},"excerpt":{"rendered":"The modern data stack might already be the new legacy. In response, Google Cloud is rebuilding for a…\n","protected":false},"author":2,"featured_media":20641,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[179,7493,14472,396,13592,14471],"class_list":{"0":"post-20640","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-agentic-ai","8":"tag-agentic-ai","9":"tag-agentic-artificial-intelligence","10":"tag-is-the-modern-data-stack-already-legacy-infrastructure","11":"tag-siliconangle","12":"tag-thomas-godwin","13":"tag-with-agents-on-the-rise"},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/20640","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=20640"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/20640\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/20641"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=20640"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=20640"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=20640"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}