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

[wpli_login_link class='et_pb_button et_pb_button_0 et_pb_module et_pb_bg_layout_dark' text='Download this Case Study' redirect = 'https://www.tredence.com/case-study/helped-a-global-retailer-develop-a-unified-customer-data-platform-on-google-cloud-as-a-foundation-for-next-best-experience?download=true']