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Modernizing Data Infrastructure for Scalable Analytics in Manufacturing
  1. case
  2. Modernizing Data Infrastructure for Scalable Analytics in Manufacturing

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Modernizing Data Infrastructure for Scalable Analytics in Manufacturing

n-ix.com
Manufacturing
Automotive
Consumer Products & Services

Data Processing Challenges in Manufacturing Operations

The client struggled with inefficient processing of large volumes of logistics and production data from factories. Legacy systems (MS SQL Server) lacked scalability, leading to high costs and slow insights. A unified, cost-effective platform was needed to handle growing data demands.

About the Client

A 130-year-old leader in automotive equipment, industrial technology, and consumer products with 400,000+ employees globally

Key Objectives for Data Infrastructure Modernization

  • Consolidate data into a scalable cloud-native platform
  • Reduce operational costs while handling 5x data growth
  • Accelerate data processing using modern analytics tools
  • Enable automated documentation of data lineage

Core System Capabilities

  • Migration to Databricks for distributed processing
  • Azure Synapse integration for data warehousing
  • DBT implementation for cross-platform transformations
  • Azure Data Factory for pipeline orchestration
  • Automated data lineage tracking and cost monitoring

Target Technology Stack

Databricks
Azure Synapse
Data Build Tool (DBT)
Azure Data Factory
Azure DevOps

System Integration Needs

  • Oracle (Redlake) legacy systems
  • Azure Log Analytics for monitoring
  • CI/CD pipelines for DevOps automation

Operational Requirements

  • Horizontal scalability for 5x data growth
  • Sub-10% annual cost increase despite scaling
  • Real-time pipeline monitoring and alerting
  • Role-based access control for data security

Expected Business Impact of Data Infrastructure Modernization

The solution will enable 5x data processing capacity with only 10% annual cost growth, reduce pipeline execution time by 70%, and provide full visibility into data lineage. The client will gain agile analytics capabilities to support real-time decision-making across global operations while maintaining strict cost controls.

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