Despite its potential, big data in catalysis faces several challenges:
1. Data Quality: Ensuring the accuracy, consistency, and reliability of data is crucial for meaningful analysis. 2. Data Integration: Merging data from diverse sources can be complex and time-consuming. 3. Computational Resources: Analyzing large datasets requires significant computational power and storage. 4. Expertise: Interpreting big data requires expertise in both catalysis and data science, which can be a rare combination.
