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	<title>Google agentic data cloud Archives - Tax Heal</title>
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		<title>The new Agentic Data Cloud helps make sense of your data.</title>
		<link>https://www.taxheal.com/the-new-agentic-data-cloud-helps-make-sense-of-your-data.html</link>
		
		<dc:creator><![CDATA[CA Satbir Singh]]></dc:creator>
		<pubDate>Fri, 01 May 2026 10:04:31 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Cross cloud lakehouse gcp]]></category>
		<category><![CDATA[Data agent kit google]]></category>
		<category><![CDATA[Google agentic data cloud]]></category>
		<category><![CDATA[Google Cloud]]></category>
		<guid isPermaLink="false">https://www.taxheal.com/?p=126531</guid>

					<description><![CDATA[<p> The new Agentic Data Cloud helps make sense of your data. The new Agentic Data Cloud helps make sense of your data. An AI agent is only as helpful as the information it understands. We’re introducing the Agentic Data Cloud as a completely new way of organizing your data so AI can take action in real time.… <span class="read-more"><a href="https://www.taxheal.com/the-new-agentic-data-cloud-helps-make-sense-of-your-data.html">Read More &#187;</a></span></p>
]]></description>
										<content:encoded><![CDATA[<h2 style="text-align: center;" data-block-key="od33e"> The new Agentic Data Cloud helps make sense of your data.</h2>
<p><img fetchpriority="high" decoding="async" class="aligncenter" src="https://storage.googleapis.com/gweb-uniblog-publish-prod/images/GCNEXT2026_0422_095514-0677_ALIV.width-1000.format-webp.webp" alt=" The new Agentic Data Cloud helps make sense of your data." width="591" height="394" /></p>
<p>The new Agentic Data Cloud helps make sense of your data.</p>
<p data-block-key="5seg6">An AI agent is only as helpful as the information it understands. We’re introducing the <a href="https://cloud.google.com/blog/products/data-analytics/whats-new-in-the-agentic-data-cloud" target="_blank" rel="noopener">Agentic Data Cloud</a> as a completely new way of organizing your data so AI can take action in real time. The Knowledge Catalog acts like a dynamic map of your entire business. Using Gemini, it autonomously tags and connects the dots across your enterprise so your agents actually understand the unique context and lingo of your company.</p>
<p data-block-key="66os5">The Agentic Data Cloud also includes Cross-Cloud Lakehouse, because you shouldn&#8217;t have to move all your data to use our AI. Standardized on Apache Iceberg, this lets you leave your data exactly where it is — even if it&#8217;s in AWS — and query it instantly, with zero friction.</p>
<p data-block-key="66os5"><img decoding="async" class="aligncenter" src="https://storage.googleapis.com/gweb-cloudblog-publish/images/GCN26_102_BlogHeader_2436x1200_Opt_16_Dark.max-2500x2500.jpg" alt="What's New in the Agentic Data Cloud | Google Cloud Blog" width="573" height="282" /></p>
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<p data-path-to-node="0">It’s a massive shift in how we think about storage. Historically, data clouds were essentially &#8220;passive libraries&#8221;—you put data in, and humans (or static dashboards) went in to find it.</p>
<p id="p-rc_9bfd625e470c79fb-183" data-path-to-node="1"><span class="citation-588">The </span><b data-path-to-node="1" data-index-in-node="4"><span class="citation-588">Agentic Data Cloud</span></b><span class="citation-588 citation-end-588">, specifically the one Google Cloud just unveiled at Next &#8217;26, flips that.</span> It’s designed to be a <b data-path-to-node="1" data-index-in-node="119">&#8220;System of Action&#8221;</b> rather than just a system of record. <span class="citation-587 citation-end-587">Instead of waiting for a person to run a query, the architecture is built so AI agents can autonomously reason over, navigate, and act on that data.</span></p>
<p>&nbsp;</p>
<p data-path-to-node="2">Here are the three biggest pillars making that happen:</p>
<p data-path-to-node="2">
<h4 data-path-to-node="3">1. The Knowledge Catalog</h4>
<p id="p-rc_9bfd625e470c79fb-184" data-path-to-node="4">This is the evolution of the old Dataplex. <span class="citation-586">It doesn&#8217;t just list where your tables are; it uses a semantic layer to understand </span><b data-path-to-node="4" data-index-in-node="126"><span class="citation-586">business meaning</span></b><span class="citation-586 citation-end-586">.</span></p>
<p>&nbsp;</p>
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<p id="p-rc_9bfd625e470c79fb-185" data-path-to-node="5,0,0"><b data-path-to-node="5,0,0" data-index-in-node="0"><span class="citation-585">Context for Agents:</span></b><span class="citation-585 citation-end-585"> If an agent is tasked with &#8220;reducing churn,&#8221; it needs to know exactly which column defines a &#8220;customer&#8221; and what &#8220;churn&#8221; means in your specific business logic.</span></p>
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<p id="p-rc_9bfd625e470c79fb-186" data-path-to-node="5,1,0"><b data-path-to-node="5,1,0" data-index-in-node="0">Continuous Enrichment:</b><span class="citation-584 citation-end-584"> It tags unstructured data (like PDFs and images) and infers missing structures, so agents aren&#8217;t &#8220;flying blind&#8221; when they hit messy datasets.</span></p>
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<h4 data-path-to-node="6">2. Model Context Protocol (MCP) Support</h4>
<p id="p-rc_9bfd625e470c79fb-187" data-path-to-node="7">Google and Snowflake have both leaned heavily into <b data-path-to-node="7" data-index-in-node="51">MCP</b>. <span class="citation-583 citation-end-583">This is a secure, universal interface that lets an agent &#8220;talk&#8221; to different data engines (BigQuery, Spanner, etc.) without needing a custom integration for every single one.</span> It treats your data assets as tools that the agent can discover and use on the fly.</p>
<p>&nbsp;</p>
<h4 data-path-to-node="8">3. <span class="citation-582 citation-end-582">The &#8220;Borderless&#8221; Lakehouse</span></h4>
<p id="p-rc_9bfd625e470c79fb-188" data-path-to-node="9"><span class="citation-581">One of the coolest technical hurdles they’ve cleared is the </span><b data-path-to-node="9" data-index-in-node="60"><span class="citation-581">cross-cloud latency</span></b><span class="citation-581 citation-end-581"> problem.</span> <span class="citation-580">The Agentic Data Cloud is built to be a borderless lakehouse using things like the </span><b data-path-to-node="9" data-index-in-node="172"><span class="citation-580">Apache Iceberg REST Catalog</span></b><span class="citation-580 citation-end-580">.</span> This allows for &#8220;zero-copy&#8221; access—meaning an agent can work across Google Cloud, AWS, and Snowflake simultaneously without the data ever being physically moved or siloed.</p>
<p>&nbsp;</p>
<p id="p-rc_9bfd625e470c79fb-189" data-path-to-node="10"><b data-path-to-node="10" data-index-in-node="0"><span class="citation-579">The big takeaway:</span></b><span class="citation-579"> We&#8217;re moving from &#8220;Data as a Resource&#8221; to </span><b data-path-to-node="10" data-index-in-node="60"><span class="citation-579">&#8220;Data as Context.&#8221;</span></b><span class="citation-579 citation-end-579"> If you&#8217;re building agents, the quality of their work is now entirely dependent on how well this data layer can explain itself to them.</span></p>
<h4>Read more</h4>
<p><strong>for more refer Artificial Intelligence  website <a href="https://indiaai.gov.in/" target="_blank" rel="noopener">click here</a></strong></p>
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<p><strong>Your Queries solved</strong></p>
<p>Google agentic data cloud,<br />
Google Cloud,<br />
Data agent kit google,<br />
Cross cloud lakehouse gcp,</p>
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