Good Data = Good AI
Many companies want to use AI, but often fail due to insufficient data quality. Yet this is precisely where the success of AI projects is decided. Without high-quality data, even the most advanced algorithms deliver unusable results. Industry experts assume that around 80 percent of the effort in AI initiatives goes into the cleansing, structuring and harmonization of data.
TheIndustriemagazin addresses this topic in a recent article and shows why data quality is becoming a central success factor. The article makes clear that it is not model development, but the establishment of a consistent and accessible data foundation that accounts for the largest share of the work.
As a practical example, our collaboration with Gabriel-Chemie is presented. The focus is on how a company can use agile structures and step-by-step data harmonization to create a scalable foundation for modern production and control systems. At the same time, the article emphasizes that successful digitalization does not wait for perfection, but relies on consistent implementation. Yes, even when the data has not yet been fully standardized at the start of the project.
Further information and insights can be found in the full Industriemagazin article.
