They are two different but related topics. You can do Data Mining on Big Data for instance.
If you look at the call for papers to see the tracks of both conference, you will notice they are pretty different.
- Foundations, algorithms, models and theory of data mining
- Machine learning and statistical methods for data mining
- Mining text, semi-structured, spatio-temporal, streaming, graph, web, multimedia data
- Data mining systems and platforms, their efficiency, scalability and privacy
- Data mining in modeling, visualization, personalization and recommendation
- Applications of data mining in all domains including social, web, bioinformatics and finance
- Big Data Science and Foundations
- Big Data Infrastructure
- Big Data Management
- Big Data Search and Mining
- Big Data Security, Privacy and Trust
- Big Data Applications
Only one track covers both. Big Data Management or infrastructure has nothing to do with Data Mining, and many Data Mining algorithms are not scalable to Big Data.
Maybe your understanding of these concepts led you to think at first that these conferences are similar but they are definitely not. However, I agree that some papers could go in both, but this is the case for many other conferences.
Conference ranking doesn't mean too much when topics are different. If you work with Big Data, your paper will have more impact if published in a conference focused on Big Data because researchers in this field will more easily be reached, and opposite if you work in Data Mining.