Leveraging Customer Data for Enhanced Analytics and AI in the Lakehouse

In today’s competitive environment, the effective use of customer event data is essential for a deeper understanding of customer behaviors, preferences, and intentions. This data can greatly enhance customer and product experiences and support sophisticated, automated decision-making processes.

Yet, many companies face difficulties in fully harnessing the value of this data due to its siloed nature across various business applications and different data platforms. In a recent TDWI survey, for instance, integrating customer behavior data from multiple sources and channels was cited as a challenge by 42% of respondents—the second-biggest challenge after dealing with data integrity.

This webinar will address the main obstacles in utilizing customer event data and will outline a structured approach for data and technology teams using the data lakehouse. Topics include:

• The critical role of a customer data infrastructure (CDI) in centrally managing behavioral event data to generate a proprietary, privacy-compliant data asset for advanced analytics and AI applications
• The benefits of decoupling the functionality of the CDI from downstream business applications such as customer data platforms and other marketing platforms to ensure better data quality, reliability, and modeling standards for a diverse set of data consumers
• Strategies for effective event data centralization within the lakehouse and real-time event streaming to power downstream analytics, AI, and marketing applications
• Implementation best practices for utilizing a CDI within the Databricks Intelligence Platform, including streamlined data engineering workflows, native event streaming ingestion with Unity Catalog, and enhanced data quality observability