About the Customer:
An American department store retail chain, with more than 1,100 stores in 49 states, is invested in driving technological innovation. At the time of this engagement, the company was especially focused on creating frictionless customer experiences across digital, mobile and in their stores. They also wanted to see how cloud technology services support their efforts in managing data at scale and in real-time, while also creating better, more personalized experiences for their customers.
Customer Challenge:
Kohl’s was having several technological issues related to scalability, maintenance, performance, data recovery, disaster recovery, increased operational overheads, and governance while running their data on legacy data warehouses.They were also facing performance issues along with the high cost of the current Teradata environment.
Partner Solution:
Datametica helped the client tackle these challenges by migrating the existing on-premise Teradata and Hadoop data warehouse to GCP with a lift and shift approach. Our team established the new GCP foundation including Solution system Architecture, Cloud Provisioning (DevOps), Security, Governance, Data Architecture and CI/CD pipeline.
We then used Raven, our automated workload conversion tool, to perform data model migration, application migration, and automated code conversion/optimization. Finally, we used Pelican, our automated data validation tool, to ensure accurate cell level data validation between the source and target source system.
Impact & Result:
- End-to-end discovery
- Workload classification
- Understanding of data lineage
- Recommendation based on access patterns, data usage and workload
- Minimal involvement of SME time
- Fact-based effort estimation
