Home » Case Study »
Objective: Modernizing analytics capabilities by moving from Netezza and DataStage to GCP
The client, a US-based online florist company, using Netezza and Datastage for its data warehouse and ETL, wanted to modernize and improve analytics capability and eliminate Netezza and Datastage to improve workload performance and gain scalability.
Challenges: Performance and Scalability related concerns
The client faced a number of challenges with their on-premise legacy data warehouse, including poor performance, and the inability to handle large data volumes or to scale. The client also wanted to organize and store their ever-growing data in a secure, scalable and cost-effective manner in order to meet their business needs.
Solutions: Accelerated Migration of Netezza EDW to GCP
Datametica migrated their Netezza and DataStage completely to Google Cloud BigQuery using Datametica migration automation tools. Below are the details of the projects:
- Datametica provided the client with a detailed assessment of the current Netezza environment
- One-time historical data migration from on-premise Netezza to GCP
- Incremental data pipeline from GCS to BigQuery
- Setup Scheduling and Orchestration for in-scope workloads using Cloud Composer
- Monitoring and logging using Stackdriver
- SQL and Datastage conversion using Datametica automated Raven – Automated Conversion Tool as conversion service
- Performed Data Validation using Datametica’s Automated data validation tool – Pelican tool between existing Netezza data warehouse and Google Cloud Platform
Client Benefits: Improved performance and scalability along with advanced governance and security capabilities
- Migrate from traditional ETL and Data Warehouse to a modern cloud technology which brings security, scalability and overall performance improvements
- The highly available GCP offering now performs high-volume operations without past system constraints
- Provide the availability of advanced analytics capabilities
GCP Products Used
Datametica Products Used
