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Case Study — Carl Zeiss Vision · Precision Optics

Modernization and Migration of Lens Production Data into an Azure Lakehouse

Decomposition of a complex legacy reporting infrastructure into a scalable Azure Lakehouse.

[Data Engineering] [Production Released] [Industrial & High-Tech]

The Client

Carl Zeiss Vision International GmbH is a global leading manufacturer in precision mechanics and optics.

The Challenge

Decomposition and replacement of a highly complex, monolithic, and difficult-to-maintain legacy infrastructure with a modern, flexible cloud database system for managing the lens production line.

Our Solution

  • Infrastructure Design

    Establishment of a highly scalable Data Lakehouse based on Azure SQL, Databricks, and Delta Lake.

  • Real-Time Processing

    Implementation of Delta Live Tables (DLT) and Apache Kafka for zero-latency processing of incoming sensor data and diverse data formats (REST, MongoDB, Blob Storage).

  • Legacy Migration

    Refactoring and transitioning historical SSIS pipelines and complex T-SQL logic into scalable, clean PySpark and Spark SQL workflows.

  • Smart Analytics

    Design and deployment of structured metadata to integrate intelligent analytics models and an AI-supported search platform (Azure OpenAI + Azure AI Search).

Results

Measurable Results

Performance
A drastic reduction in data processing time by 80% (from previously 2 hours to just 15–20 minutes).
Cost-Efficiency
Successful reduction of operational cloud costs by 30% through efficient code structures.
Reliability
Reduction of system downtime to below 5% by establishing a detailed monitoring system via Azure Log Analytics.
Scalability
An increase in overall system scalability by 400%.

Schedule Consultation

Your project as the next success story.

Just like for Carl Zeiss Vision, we design, implement, and stabilize mission-critical data platforms – compliant-by-design.