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Objective: Modernization and consolidation of different applications on one platform
An American-based toy manufacturing company that manufactures toys and sells them globally. This client wanted to modernize the data warehouse ecosystem as well as consolidate the various platforms under one roof.The modernization of GCP and BigQuery brings new analytics capabilities.
This client sought a technology partner who could help them efficiently and safely modernize and thereby leverage GCP cloud-native technologies.
Challenges:
The client had been experiencing technical, scalability, and cost issues with the existing Netezza system. As part of a technology upgrade and modernization effort, the client wanted to leverage cloud-native technologies offered by Google Cloud Platform (GCP) to consolidate platforms and manage operational costs in a better way.
Solutions: Designing GCP Future State Architecture
Before Migration
- Datametica provided the client with a detailed assessment of the existing Netezza environment by using Eagle – an automated assessment & data migration planning technology – and provided the detailed migration plan.
- The legacy system application pipeline used Oracle EDW as the source and Netezza as the target, with downstreams mostly on GCP.
- The pipeline was developed using Informatica PowerCenter and Orchestration using a CA scheduler.
- Downstream systems were mostly migrated to GCP.
Migration Approach
- The original approach for migration was to simply repoint the PC WFs to GBQ.
- However, during the migration and repointing, the Datametica team observed that PCs have limitations with respect to BQ and that their performance is also poor.
- To address the limitations and performance issues, the Datametica team converted the required PC WFs either into BQ Store Procedures (SP) or IICS.
- During the OPA module implementation, the Datametica team discovered that the OPA module is a full read and load, which was unnecessary. As a result, the Datametica team converted the flow from FULL LOAD to incremental, optimizing the overall solution and lowering maintenance costs.
- The FAP module of Netezza was one of the complex modules with critical downstream dependencies. While the client’s expectation was to make sure 100% of the data and report matched.
- To handle complexities in data matching, the Datametica team used a hybrid approach by converting the WFs into SPs or IICS.
- Performed data validation using the Datametica Automated Data Validation Technology – Pelican between Netezza, and BigQuery.
Client Benefits: Faster Cloud Migration, Greatly Enhanced Analytics Capabilities, and Lower Operation Costs
- Reduced operational costs and infrastructure provisioning timelines.
- Improvements in efficiency and performance are due to the consolidation of different legacy applications into a single, unified GCP.
- Datametica solutions delivered faster cloud migration, with lower costs and lower business risk.
- Ensured confidence in the decommissioning of Netezza Warehouses with the help of Pelican.
DM Product Used
GCP Product Used
