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    <title>topic Announcement | Introducing CustomerLake: The Agentic CDP embedded in Databricks in Announcements</title>
    <link>https://community.databricks.com/t5/announcements/announcement-introducing-customerlake-the-agentic-cdp-embedded/m-p/162855#M915</link>
    <description>&lt;P&gt;&lt;SPAN&gt;Databricks has introduced &lt;/SPAN&gt;&lt;STRONG&gt;CustomerLake&lt;/STRONG&gt;&lt;SPAN&gt;, an &lt;/SPAN&gt;&lt;STRONG&gt;Agentic CDP&lt;/STRONG&gt;&lt;SPAN&gt; built directly in the Databricks lakehouse to help marketing and data teams unify customer data, activate audiences, and personalize experiences without moving or duplicating sensitive data.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;FONT size="4"&gt;&lt;STRONG&gt;What’s new&lt;/STRONG&gt;&lt;/FONT&gt;&lt;/P&gt;
&lt;UL&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;A CDP embedded in Databricks&lt;/STRONG&gt;&lt;SPAN&gt; – CustomerLake brings core CDP capabilities like Customer 360, identity resolution, audience building, activation, and personalization directly to the governed data foundation teams already use.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Profile Agents for customer data readiness&lt;/STRONG&gt;&lt;SPAN&gt; – Profile Agents help teams prepare raw customer data, identify quality issues, and unify fragmented records into trusted customer profiles directly in Databricks.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Campaign Agents for always-on engagement&lt;/STRONG&gt;&lt;SPAN&gt; – Campaign Agents help marketers build audiences, recommend next-best actions, activate across channels, and optimize around business goals using governed customer context.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Built to reduce martech sprawl&lt;/STRONG&gt;&lt;SPAN&gt; – Databricks positions CustomerLake as a way to avoid extra data copies, separate activation layers, and disconnected CDP systems by keeping customer data, AI, and governance in one place.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Open across the existing ecosystem&lt;/STRONG&gt;&lt;SPAN&gt; – CustomerLake is designed to work with existing martech and adtech tools, with federated access to trusted customer data across systems like Databricks, Snowflake, BigQuery, cloud object storage, and operational databases.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;P&gt;&lt;SPAN&gt;At the center of the launch is the idea of moving from static campaigns to more continuous, agent-driven engagement. Databricks describes this as &lt;/SPAN&gt;&lt;STRONG&gt;Infinity Campaigns&lt;/STRONG&gt;&lt;SPAN&gt;: always-on loops that analyze signals, decide the next best action, and adapt across audiences, offers, and channels.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="p8i6j01 paragraph"&gt;&lt;A style="background-color: #ff3621; color: white; padding: 10px 20px; text-decoration: none; border-radius: 5px; font-weight: bold; display: inline-block;" href="https://www.databricks.com/blog/introducing-customerlake-agentic-cdp" target="_blank" rel="noopener"&gt; &lt;span class="lia-unicode-emoji" title=":backhand_index_pointing_right:"&gt;👉&lt;/span&gt; Read the full post here &lt;/A&gt;&lt;/P&gt;</description>
    <pubDate>Mon, 13 Jul 2026 17:00:08 GMT</pubDate>
    <dc:creator>Tushar_Parekar</dc:creator>
    <dc:date>2026-07-13T17:00:08Z</dc:date>
    <item>
      <title>Announcement | Introducing CustomerLake: The Agentic CDP embedded in Databricks</title>
      <link>https://community.databricks.com/t5/announcements/announcement-introducing-customerlake-the-agentic-cdp-embedded/m-p/162855#M915</link>
      <description>&lt;P&gt;&lt;SPAN&gt;Databricks has introduced &lt;/SPAN&gt;&lt;STRONG&gt;CustomerLake&lt;/STRONG&gt;&lt;SPAN&gt;, an &lt;/SPAN&gt;&lt;STRONG&gt;Agentic CDP&lt;/STRONG&gt;&lt;SPAN&gt; built directly in the Databricks lakehouse to help marketing and data teams unify customer data, activate audiences, and personalize experiences without moving or duplicating sensitive data.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;FONT size="4"&gt;&lt;STRONG&gt;What’s new&lt;/STRONG&gt;&lt;/FONT&gt;&lt;/P&gt;
&lt;UL&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;A CDP embedded in Databricks&lt;/STRONG&gt;&lt;SPAN&gt; – CustomerLake brings core CDP capabilities like Customer 360, identity resolution, audience building, activation, and personalization directly to the governed data foundation teams already use.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Profile Agents for customer data readiness&lt;/STRONG&gt;&lt;SPAN&gt; – Profile Agents help teams prepare raw customer data, identify quality issues, and unify fragmented records into trusted customer profiles directly in Databricks.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Campaign Agents for always-on engagement&lt;/STRONG&gt;&lt;SPAN&gt; – Campaign Agents help marketers build audiences, recommend next-best actions, activate across channels, and optimize around business goals using governed customer context.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Built to reduce martech sprawl&lt;/STRONG&gt;&lt;SPAN&gt; – Databricks positions CustomerLake as a way to avoid extra data copies, separate activation layers, and disconnected CDP systems by keeping customer data, AI, and governance in one place.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Open across the existing ecosystem&lt;/STRONG&gt;&lt;SPAN&gt; – CustomerLake is designed to work with existing martech and adtech tools, with federated access to trusted customer data across systems like Databricks, Snowflake, BigQuery, cloud object storage, and operational databases.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;P&gt;&lt;SPAN&gt;At the center of the launch is the idea of moving from static campaigns to more continuous, agent-driven engagement. Databricks describes this as &lt;/SPAN&gt;&lt;STRONG&gt;Infinity Campaigns&lt;/STRONG&gt;&lt;SPAN&gt;: always-on loops that analyze signals, decide the next best action, and adapt across audiences, offers, and channels.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="p8i6j01 paragraph"&gt;&lt;A style="background-color: #ff3621; color: white; padding: 10px 20px; text-decoration: none; border-radius: 5px; font-weight: bold; display: inline-block;" href="https://www.databricks.com/blog/introducing-customerlake-agentic-cdp" target="_blank" rel="noopener"&gt; &lt;span class="lia-unicode-emoji" title=":backhand_index_pointing_right:"&gt;👉&lt;/span&gt; Read the full post here &lt;/A&gt;&lt;/P&gt;</description>
      <pubDate>Mon, 13 Jul 2026 17:00:08 GMT</pubDate>
      <guid>https://community.databricks.com/t5/announcements/announcement-introducing-customerlake-the-agentic-cdp-embedded/m-p/162855#M915</guid>
      <dc:creator>Tushar_Parekar</dc:creator>
      <dc:date>2026-07-13T17:00:08Z</dc:date>
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