Unlocking Personalized Engagement with a Modern Data Platform

Challenge

The company’s legacy data warehouse was costly, rigid, and only accessible to a small group within IT. Business teams couldn’t move fast enough to respond to changing customer behavior, and the growing demand for personalized experiences put pressure on outdated systems.

Solution

A new data science team took initiative by building a data lake on Google Cloud Platform and launching an analytics sandbox. Early AI-driven use cases showed promise—but scaling the solution across the business required more structure.

Productive Edge partnered with the business intelligence team to evolve the data lake into a modern enterprise data platform. This included:

• Defining an enterprise roadmap for broader adoption

• Redesigning the BI team’s role to focus on enablement

• Establishing a data governance framework that supported both access and compliance

• Building a master data strategy and operational model for MLOps and DataOps

Results

The client successfully shifted from siloed analytics to a modern, scalable data platform. The new model empowered teams across the business to generate insights, launch AI use cases faster, and personalize customer engagement at scale.

Key Metrics

• 4x increase in data access across business units

• 60% faster delivery of AI-driven use cases

• Full DevOps and governance support enabled for ongoing scale