Datansh helped a light manufacturing enterprise replace manual spreadsheets and end-of-day reporting with a near-real-time Azure and Power BI analytics foundation that improved yield visibility, reduced scrap, and gave plant teams faster control over production issues.
97–99% printer yield visibility with printer performance tracked near real time.
92%+ thermal yield baseline with clear visibility into a key cost-optimization area.
Minutes instead of next shift for issue detection and intervention on resistance, nozzle, and flow-rate abnormalities.
Before modernization, the plant relied on manual spreadsheets and end-of-day reporting. Production and defect data were visible only the next day, root-cause analysis was harder, defects were discovered late, and accountability at operator, nozzle, syringe, or batch level was limited.
Datansh built a near-real-time reporting and data engineering backbone using Azure SQL, Azure Data Factory, staging layers in Blob Storage and Data Lake, and a Power BI semantic model. The output was displayed on large digital screens on the shop floor so supervisors, operators, and engineers could act immediately on production deviations.
More work in manufacturing and adjacent operational environments.
Datansh helped a U.S.-based light manufacturer transform long, unstructured CRM conversation histories into predictive next-action intelligence, giving sales reps and managers faster clarity on how to move enterprise deals forward.
Datansh helped a multinational tyre manufacturing organization move from disparate, semi-structured data flows to a centralized batch-and-streaming platform that treated data as a product and improved enterprise reporting reliability.
Datansh helped a U.S.-based multinational manufacturer replace static, number-heavy ERP reporting with a secure Azure-based analytics foundation that unified legacy ERP data, connected additional enterprise sources, and turned reporting into interactive business visibility.