Helped a global retailer develop a Unified Customer Data Platform on Google Cloud as a foundation for “Next Best Experience”

CASE STUDY

Helped a global retailer develop a Unified Customer Data Platform on Google Cloud as a foundation for “Next Best Experience”

SUMMARY

Client ranks amongst the world’s largest retailers. They had large volumes of customer data lying across disparate systems catering to different sales channels. Their current Hadoop-based infrastructure was unable to handle the workload.
They wanted to:
• Create a single source of truth across all existing internal data-platforms
• Integrate a powerful design to reduce time taken to convert data into insights
• Leverage AI/ML to make effective customer life cycle strategies

APPROACH

The approach to address the client’s challenge included:

Building re-usable data pipelines to move away from the current Hadoop-based system to GCP
Leveraging the GCP environment to build a cost-optimized ecosystem to cater to both the business users and the data-scientist community
Merging demographics, customer, geo-location, credit-model, clickstream & marketing campaign data to create a single source of truth

Using a model management on GCP to track and maintain 150+ ML models

KEY BENEFITS

Our solution helped the client:

Develop an auto-scalable infrastructure on GCP to manage variable workloads thus reducing cost
Use big-query and data-proc in tandem to provide compute-horsepower on a case-to-case basis based on cost
Leverage Kubeflow and Kubernetes for model management and deploying model endpoints for down-stream consumption

RESULTS

The UDP since its inception has been processing 250 TBs (Terabytes) of data weekly
Overall reduction of processing time in computation-intensive jobs by 70 percent
Overall costs reduced by 30-35 percent

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