"Our work force is now able to explore and analyse the data to better understand the production processes, which in turn allows for process development, giving better performance, higher throughput and increased yield. It importantly, it puts the process owner in control."
- Jonathan Williams (IQE)
Interest is growing in data literacy and the opportunity to bring about efficiency and effectiveness through the better exploitation of data.
We’ve all heard the promises, but gaining an advantage from data-driven methods is somewhat different. Success requires the integration of data management, data analysis and subject matter expertise, plus the ability to communicate findings with brevity and simplicity. Understanding the circumstances under which our data has been collected, how it has been measured, and its potential limitations, are foundations of the process of extracting maximum information from our data.
You’ll find guidance and stories about how to get started with machine learning techniques or effectively integrate them within existing programs that seek to make the most of your data and drive more value for your organization. We speak to:
- Jonathan Williams, Data Analysis Manager at IQE about data preparation and visualisation in product development.
- Florian Vogt, Senior System Engineer at JMP about the different modelling techniques.
- Massimo Martucci, Senior System Engineer at JMP about the difference between correlation and causation.
- The importance of using domain knowledge, experience, and intuition alongside statistical and machine learning methods.
- Understanding the impact data quality, structure and resolution have upon the questions we can answer from our data.
- A data-driven process for enhancing our learnings.
- The impact data-driven processes have on our outcomes in research, development, technology transfer, and production projects.