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With Databricks CustomerLake, HP configured governed data models and published attributes on top of its existing Databricks setup, completing audience readiness in just 2 hours on first use; by comparison, a traditional CDP takes 2 to 3 months. HP estimates that integrating CDP capabilities can reduce total cost of ownership by up to 40%, that 90% of marketing signals are net-new, and that intent data coverage expanded from 75 topics to about 20,000. HP also brought identity signals back into the Databricks environment and used AI/BI Genie and a semantic layer to support self-service analytics and agents. This information comes from an article published on the Databricks Blog on October 20, 2026; no subsequent developments have been seen.
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How HP Built an AI-Ready CDP with Databricks CustomerLakeDevelopments
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HP achieves audience readiness in two hours with Databricks CustomerLake
Source:Databricks Blog
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Oct 20
Databricks BlogFirst-party
How HP Built an AI-Ready CDP with Databricks CustomerLake
Using Databricks CustomerLake, HP configured governed data models and published attributes on top of its existing Databricks deployment, achieving audience readiness in 2 hours on first use, compared with 2-3 months for a traditional CDP. HP estimates that consolidating CDP capabilities reduces total cost of ownership by up to 40%, that 90% of marketing signals are net-new, and that intent data coverage expanded from 75 topics to about 20,000. HP also brought identity signals back into the Databricks environment and uses AI/BI Genie and a semantic layer to support self-service analytics and agents.