5 Pillars of a Solid Industrial Analytics Solution

A core requirement of analytics value is connectivity to modern data sources, plant devices and enterprise applications (MES, SCADA, ERP, CRM etc.) via standard industry protocols, but also in-place brownfield manufacturing databases that may have evolved from operating support systems over decades. Since these assortments of data repositories can rarely be kept to the latest, greatest architecture and open connectors, a desirable solution should provide both modern and legacy, proprietary connectors, or mechanisms to exchange data to a broad range of IoT and Analytical systems. In addition, a mature industrial analytic solution should be aware of the challenges of capture time, data quality (or status) and value when provided from smart sensors

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Have you identified high impact use cases that support your industrial transformation or digital efforts?
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If so, what area of your operation are the biggest priorities?
Workforce Productivity Operational Insights Real-time Production Monitoring Other

What is the most critical industrial digital transformation challenge your organization is trying to resolve?
Free your operations from manual data entry and paper-based procedures Connect legacy equipment to a single digital platform collecting

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