When discussing big data, it is sometimes mentioned that data modeling can be done by using a tool like map reduce, while data processing may be performed by apache spark. What is the difference between data modeling tasks, and data processing tasks? Thanks in advance
- Data modeling means representing the data, usually with a somewhat compact model. Modeling implies simplifications: this can lead to a good model which reliably represents the patterns in the data or a terrible model which simplifies too much or not enough.
- Data processing is applying any kind of process to the data.
For the record, map-reduce is relevant only as a technique for processing large data efficiently.