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Elevating Retail Data Analytics: Legacy 1010 to GCP Migration Success

Client Overview:

A major US retailer with numerous discount stores, providing a wide range of everyday essentials, household items, and seasonal products at competitive prices, sought to retire their outdated 1010 data platform. The goal was to reduce overall operational costs while enhancing their data science and analytics capabilities for future-ready business insights.

Business Challenges:

  • Multiple data platforms have been built over the years to address specific analytics needs.
  • Online and offline business performance were not integrated, despite operational overlaps aimed at enhancing the overall customer experience.
  • KPIs on the 1010 platform did not align with internal BI reports, causing a trust deficit and forcing teams to spend hours reconciling data and business logic.
  • An excess of KPIs and reports served the same users, leading to integrity challenges and further trust issues.
  • Maintaining the 1010 platform had become costly, and implementing changes and enhancements required significant time.
  • The analytics development cycle was prolonged due to the complex reporting environment and a lack of self-service capabilities.

Tredence Solution:

    Architected a modern data platform on GCP Cloud, leveraging all GCP native services. Reverse engineered 100+ base tables, 250+ views, 150+ MT objects, and 2,500+ queries, and reports to retrofit 1010 datasets into a modern, enterprise-scale retail data model. Migrated around 100+ key sales, inventory, pricing, and customer insights leveraging BigQuery and Looker.

Why GCP?

  • GCP's proven expertise in network optimization was critical for handling the very high data volume, making it a better choice over Azure.
  • Competitive pricing among hyperscalers.
  • Availability of a highly scalable, Gen-AI-enabled native data warehousing and analytics environment.
  • Need for comprehensive and performance-efficient enterprise analytics services.

GCP Services Leveraged:

  • Cloud Storage
  • Cloud Data Proc
  • Cloud SQL
  • BigQuery
  • Cloud Composer
  • Looker

Relevant Accelerators:

  • T-Discoverer
  • T-Ingestor
  • T-Analyzer
  • Dquest

Impact Delivered

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Over 50% migration effort saved through accelerators.

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Over 80% platform cost savings monthly.

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More than 20,000 support (ops) hours saved in the first year.

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50-70% improvement in response time for critical sales reports.

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