In SAS Viya, a data scientist wants to perform distributed text analytics on 2 million documents. Which architecture advantage does running PROC TEXTMINE in SAS Viya CAS provide over traditional SAS 9.4?
Select an answer to reveal the explanation.
Short Explanation
Here's the deal — running PROC TEXTMINE in CAS is right because it spreads the huge term-document matrix and SVD work across worker nodes, so you can handle millions of documents without blowing past one machine's memory.
Full Explanation
The correct advantage is that CAS distributes the term-document matrix computation and singular value decomposition across multiple worker nodes, which lets you process document corpora that would exceed single-machine memory in SAS 9.4 and overcomes the single-machine memory and compute limitations of SAS 9.4 Workspace Server execution. The deep learning embeddings claim is wrong because CAS PROC TEXTMINE uses the same statistical text mining methods by default, not automatic deep learning embeddings unavailable in SAS 9.4. The stop word removal claim is wrong because stop word lists are still applicable in CAS, and neural language models are not required to eliminate them. The 10x topics claim is wrong because the number of topics is a parameter, not a CAS versus SAS 9.4 distinction.