Customer
Large retailer company with 25000+ physical supermarkets and 55+ million clients.
Challenge
Timely collection of huge data volumes and transformation of raw data from multiple sales points into comprehensive insights and analytics.
Project Results
Project team has implemented several data pipelines, feeding ~200 staging tables from several source systems, and transforming raw data into the aggregated measurements stored in 45 data marts within the Client's DWH.
Business Value
Improved analytics for such areas as goods logistics, finance and HR.
Tech Stack
Python (Pandas, Xgboost, Matplotlib), Airflow, Kubernetes, Jenkins, Clickhouse.
Large retailer company with 25000+ physical supermarkets and 55+ million clients.
Challenge
Timely collection of huge data volumes and transformation of raw data from multiple sales points into comprehensive insights and analytics.
Project Results
Project team has implemented several data pipelines, feeding ~200 staging tables from several source systems, and transforming raw data into the aggregated measurements stored in 45 data marts within the Client's DWH.
Business Value
Improved analytics for such areas as goods logistics, finance and HR.
Tech Stack
Python (Pandas, Xgboost, Matplotlib), Airflow, Kubernetes, Jenkins, Clickhouse.