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ManufacturingData Engineering

Data Modernization for a Manufacturing Enterprise

Global Manufacturing Enterprise
22 weeks engagement
55% reduction
in data infrastructure costs
10x improvement
in query performance
6 hours → 12 minutes
nightly data refresh time
Zero downtime
during migration with parallel running

The Challenge

A global manufacturer with 15 production facilities was running its analytics on a 12-year-old on-premise data warehouse. Query performance was degrading, maintenance costs were escalating, and the platform couldn't support modern AI/ML workloads.

Before Saks Tech

The legacy Oracle warehouse took 6+ hours for nightly ETL. Simple queries took minutes. No support for streaming data. The data team spent 70% of their time on maintenance rather than analytics.

Our Solution

Saks Tech led a phased migration to a modern cloud data lakehouse architecture, preserving all existing reports while enabling new analytical capabilities. We implemented incremental data loading, real-time streaming, and self-service data access.

Results Delivered

55% reduction
in data infrastructure costs
10x improvement
in query performance
6 hours → 12 minutes
nightly data refresh time
Zero downtime
during migration with parallel running

The migration was the smoothest large-scale infrastructure project we've ever done. Our data team is finally building analytics instead of fixing pipelines.

James Park
Director of Data Engineering, Global Manufacturing Enterprise

Technology Stack

SnowflakedbtApache KafkaTerraformAzure Data Lake

Services Used

Data Engineering
Data Analytics
Consulting Services

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