Data quality and data-driven decisions: Challenges & Opportunities | Series: Spotlight

In the current issue of "Dataciders Spotlight", Melanie Sigl, Managing Consultant at PRODATO, a company of the Dataciders Group, talks about her focus in the areas of machine learning and artificial intelligence - and about what is currently particularly important to companies.

Many organizations are faced with the challenge of modernizing their data infrastructure, improving the quality of the database and implementing AI applications on a large scale at the same time. A key issue here is dealing with distributed data silos, which often stand in the way of efficient analysis.

In addition to the much-discussed generative AI, aspects such as the explainability of algorithms, legal frameworks (e.g., through the AI Act), and the targeted improvement of data quality are also becoming increasingly important.

Using a specific project from the chemical industry, Melanie shows how AI can be used in a scalable way: A digital twin was developed in the Azure Cloud that maps more than 3,000 large industrial plants worldwide. The technical challenge was to combine different sensor data types and models and to flexibly implement individual workflows for data pre-processing and training for each plant. The result was a successful and sustainable cloud rollout.