Data Catalog and Dashboard Design for Manufacturing Analytics
Modern data-driven organizations rely on up-to-date information for precise, timely decision-making. In the manufacturing industry, using real-time data helps optimize and control processes, ensuring consistent product quality and building trust with customers. Advanced data management technology is now essential—improving production quality, connecting process data across the organization, and driving operational excellence.
No Time Limit
Submit evidence anytime, no deadlines
Self-Paced
Progress at your own pace and schedule
2 Submission Quotas
Revised your submission with feedback
Competency
Earner designs a data catalog and dashboard to monitor and support functions related to production process management.
How ?
Earner identifies key performance indicators (KPIs) and performs the Extract, Transform, and Load (ETL) process to design a data catalog and dashboard.
Method overview
- Defining key performance indicators (KPIs) and identifying their data sources.
- Creating a data pipeline diagram.
- Designing a data catalog.
- Performing Extract, Transform, and Load (ETL) processes.
- Designing a dashboard that aligns with the data catalog.
How can you achieve ?
- Submit a data pipeline diagram that shows the flow of data within your own function and related departments.
- Submit a data catalog table that includes three key components.
- Submit a video presentation that demonstrates the alignment between the dashboard and the data catalog.
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Guidelines are now available in Thai
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Unlimited Access to Competency Guidelines
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2 Submission Quotas to Verify Competency
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Personalized Feedback
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Digital Badge
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Shareable to Social Network
Learning unit will be coming soon!
Currently, this micro-credential is available only with the Verify plan.
What will you get ?
Digital Badge
Data Catalog and Dashboard Design for Manufacturing Analytics
Issued by KMUTT | You will earn this digital badge after you have completed this Micro-credential.
- Show your real works as the competency evidence
- Sharable with an attachment of assessor’s recommendation letter
- Verified by educational / industrial experts
Who is this for ?
Who work in the field of production process management in organizations or Industrial IT groups or Industrial Software Developers
Who developed this ?
Asst. Prof. Dr. Diew Koolpiruk, Dr. Teema Leangarun
Asst. Prof. Dr. Diew Koolpiruk
Assistant to the President for Digital Transformation
Professor at Department of Control System and Instrumentation Engineering (INC), KMUTT
Expertise/ Experiences:
Manufacturing Execution Systems, Automation System, Data Analytics, Artificial Intelligence (AI)
Dr. Teema Leangarun
Professor at Department of Control System and Instrumentation Engineering (INC), KMUTT
Expertise/ Experiences:
Manufacturing Execution Systems, Automation System, Data Analytics, Artificial Intelligence (AI)