Python-based platforms like Pandas or Spark are very good too at displaying data and do exploratory analysis. I definitely prefer them to SAS EG. It's just too slow, and doesn't let you peek into the data very easily. Lots of clicking, and I'd rather just write some code, …
Although not used in the enterprise, I have used Anaconda Python to shape and cleanse data from Excel reports that was too difficult for SAS to complete. The object oriented nature and the Pandas package made ingestion of the data and reshaping more useful in this use case. Anac…
SAS EG has better Graphical User Interface to build project trees and help users to create data queries/calculations. SAS EG can handle bigger data sets compared to other programs. You can easily clean the data sets and manipulate the data. It is easier to send the project tree …
Why I prefer SAS EG: Data processing speed is much faster than that R Studio. It can load any amount of data and any type of data like structured or unstructured or semi-structured. Its output delivery system by which we have the output in PDF file makes it very comfortable to …
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Chose SAS Enterprise Guide
It gives more flexibility in terms of writing codes, and you're able too see expected output and then you go on to modify
Of the software tools I have tried, SAS Enterprise Guide is my preferred choice because of the efficiency of processing, the line-by-line processing, the ease of writing code, and the customer support. SAS appears to have put lots of effort into making SAS Enterprise Guide one …
I haven't used SPSS myself but from what I was told, integration of data was much more limited and not easy to used. Also, the number of people with SPSS knowledge is less than the number of SAS users so finding workforce can be an issue. The whole SAS solution just made much …