Case Details

Empowering the Integrated Circuit Industry with Faster, more Accurate Insights

Problem Statement

Support for seamless processing of data for predictive performance & analytics and management of resources.

Improving imaging techniques for better fault detection in the production line.

Data is constantly clicked from a vast Silicon Disk that requires ingestion, compilation, and analysis to generate.

Required a cost-effective solution for scalable storage and big data analytics capabilities for end-to-end management of data.

Needed streamlining of IC quality control processes.

Efficient handling of large amounts of data in a stable, low-latency, and secure manner was becoming a challenge.


Solution Offered!


Data Migration Flow
  • Secure ETL streams were created using advanced Azure PaaS services.
  • Ensuring application security by providing user, device, and programmatic access while enabling authentication to other services. Using a secure virtual network tunnel to access all internal endpoints, and tracking every activity through audit logs and respective security alerting.
  • Enabled Azure Data Factory for seamless transition of data across various Azure cloud services and performed multiple operations on data. Also, supported easy migration of ETL workloads.
  • For security management, Azure Active Directory, Managed Identity (MI) was used to prevent key management processes, and Virtual Network (VNET) for isolation of data and endpoints was preferred.
  • Configured monitoring and alerts on ADF pipelines functionalities stages on the basis of various filters, supported with notifications via email, SMS, voice, and push notifications.
  • Integrated Power BI with Azure Synapse Analytics for generating and publishing reports.
  • Data storage and management via Synapse Data Warehouse and Azure Data Lake Storage.
  • xtraction of data from Silicon Disks with IoT Central by using IOT central agents installed on each Silicon Disk location’s Windows machines.
  • Data processing, filtering, and analysis using ETL Pipelines.

Final Outcomes

No loss of data while transitioning and the data source remained available whether it was active or inactive

Simplified quality assessment at every stage of data transition.

Instant alerts for any faults or issues at any stage during the Data transition

Hundreds of terabytes of data are seamlessly ingested into the ETL system on a daily basis.

Gained real-time visibility and comprehensive monitoring at every step of the data journey – from source to analysis, filtration, and visualization.

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