Data Platform Migration Delivers Significant Accuracy and Performance Improvements

About the Client

A leading American clothing retailer that offers a wide variety of apparel and accessories for both men and women. The brand is recognized for its versatile styles suitable for various occasions. The brand is part of a larger fashion company that operates several brands. The company has both physical stores and an online presence.

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The Challenge

The retail client aimed to migrate its Enterprise Data Warehouse from legacy infrastructure, addressing concerns related to aging hardware, performance, and supportability as part of ending its Teradata environment.

This project aimed to consolidate data platforms, enhance performance and reliability, and reduce operational costs. The newly established Enterprise Data Platform (EDP) is positioned to modernize various data initiatives and cloud infrastructure.

The Solution

Google Cloud infrastructure was used for deploying the EDP environment and employing Infrastructure as Code (IaC). Legacy code was translated into platform-independent coding frameworks enhancing the modernization of the data pipeline deployment. This included configuring and managing batch pipelines and implementing near real-time micro-batch processing.

BigQuery Editions slot reservations were utilized and aligning with best practices.The reporting platform, MicroStrategy, was configured and optimized for seamless integration with BigQuery.

The Result

ETL Performance Metrics include an average 641-minute aggregate performance gains; MicroStrategy (MSI) Performance gains of 52% improvement on critical reporting.

The client achieved significant advancements in its data platform, bolstering trust and attaining an impressive 99.2% data accuracy against the legacy system. The migration to GCP’s BigQuery not only reduced licensing and support costs but also enhanced stability and operational efficiencies.