Cloud technology offers industries the ability to modernize, scale, and innovate. UNLSH maximizes this potential by providing a robust platform that ensures seamless digital transformation while maintaining control, flexibility, and compliance.

‍

‍

‍

UNLSH ensures at least 25% reduction in effort and risk, associated with any Cloud Dx project:

1. Custom API Support: Many enterprises develop custom APIs to protect their confidential data. UNLSH supports these custom APIs, enabling seamless data ingestion from diverse sources such as ERP, MES applications, engineering data, and documents.
   ‍
2. Source Data Visibility: Visibility into source data is crucial for complex digital transformation projects. UNLSH offers comprehensive visibility into source data, including tables, views, schema, and data content, even before ingestion. This reduces risks, complexities, and clarifications by 80% to 90%.
   ‍
3. Time-series Process Data Historian Tag  Synchronization and Ingestion: Manufacturing, Mining and Supply-Chain operations generate lots of time-series data from PLC, DCS, SCADA, and IoT. The number of tags or time-series data points vary as new tags are added, UOM is updated, etc. Special mechanisms are needed to keep the IT/OT data hub in synch with these changes. UNLSH provides an automated synchronization process for historian tags, facilitating easy profiling, tag meta-data enhancement and harmonization (in case of multiple historians),on-demand trending, analytics, calculations, etc.
   

4. Data Pipeline Visibility: UNLSH offers intuitive visibility and search capabilities within the data pipeline, enhancing efficiency and reducing effort.
   ‍
5. Data Ownership, Security and cost optimization: UNLSH offers very flexible hybrid configuration that allows customer to distribute data between on-prem, Cloud IaaS layer and Cloud PaaS. This offers significant advantages:
   
    
   • Data Ownership – A copy of the curated data can be used to leverage highly sophisticated cloud analytics capabilities, while retaining ownership and control of the complete data.
   • Cost Optimization – UNLSH allows hybrid configurations that would ensure optimization of costs. For example, hosting of all raw data in on-prem or AWS IaaS layer and curated data and analytics on Microsoft Azure Fabric SaaS.
   • Enhanced Security – The most secure place for enterprise data is within the enterprise firewall. This has been proven time and again by major cloud data breaches. Streaming only a selected set of data to cloud PaaS / SaaS while retaining the core data set within the enterprise firewall, is the best strategy for maximizing security while exploiting the advanced cloud analytics capabilities.