Manufacturers Must Prioritize Industrial Data Governance Before AI and Analytics
- Published
- Source
- AutomationWorld.com
Manufacturers are generating unprecedented amounts of data through automation systems, capturing everything from process values to production metrics. However, many plants face challenges in quickly answering fundamental operational questions, such as equipment status during issues or alarm sequences. The root cause often lies in a lack of structured, contextualized data governance rather than insufficient data itself.
As manufacturers increasingly invest in analytics and AI, the importance of a solid data foundation becomes critical. Structured data not only aids in generating meaningful reports but also enhances AI insights. Poorly designed automation systems can lead to disorganized data, resulting in confusion and inefficiencies that erode trust among operators and complicate reporting for engineers and maintenance teams.
To address these challenges, manufacturers must focus on establishing effective data governance from the outset of automation system design. Collecting more data does not inherently create value; instead, organizing data around relevant categories is essential for it to be actionable. No further timeline was disclosed at the time of publication.
Original report
Before AI, Analytics or Dashboards: Manufacturers Need Better Industrial Data Governance
AutomationWorld.com · (Guru Thakkar)This briefing is an independently written summary based on publicly available reporting and is provided for industry information and news discovery. The original report and source publication are credited and linked where applicable. RobotToday does not claim ownership of third-party source material.
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