Session

Innovating Retail Data: Unilever’s Transformation with Databricks Lakeflow Declarative Pipelines

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Overview

Wednesday

June 11

4:10 pm

ExperienceIn Person
TypeBreakout
TrackData Engineering and Streaming
IndustryRetail and CPG - Food
TechnologiesDatabricks Workflows, DLT, Unity Catalog
Skill LevelIntermediate
Duration40 min

Retail data is expanding at an unprecedented rate, demanding a scalable, cost-efficient, and near real-time architecture. At Unilever, we transformed our data management approach by leveraging Databricks Lakeflow Declarative Pipelines, achieving approximately $500K in cost savings while accelerating computation speeds by 200–500%.By adopting a streaming-driven architecture, we built a system where data flows continuously across processing layers, enabling real-time updates with minimal latency.Lakeflow Declarative Pipelines' serverless simplicity replaced complex-dependency management, reducing maintenance overhead, and improving pipeline reliability. Lakeflow Declarative Pipelines Direct Publishing further enhanced data segmentation, concurrency, and governance, ensuring efficient and scalable data operations while simplifying workflows.This transformation empowers Unilever to manage data with greater efficiency, scalability, and reduced costs, creating a future-ready infrastructure that evolves with the needs of our retail partners and customers.

Session Speakers

Evan Cherney

/Senior Data Science Manager
Unilever